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About This Role
Overview
The Microsoft Federal organization was established to address the unique mission, legal/regulatory requirements, and procurement rules and processes of the United States Government (USG). Microsoft Federal is committed to ensuring its resources – including appropriately qualified, experienced, and certified personnel (with necessary security clearances or otherwise) are available as needed to meet USG evolving needs. To that end, Microsoft embraces, as a mission\-critical philosophy, flexibility in the recruiting, hiring, and workforce assignment of Microsoft Federal personnel. Microsoft Federal personnel can expect to serve in various roles in the Microsoft Federal organization during the course of their career to meet evolving USG needs, regardless of segment – Civilian, Defense, or Intelligence community.
We are seeking an experienced Senior Cloud Solution Architect \- Cloud \& AI Apps to join our Federal organization. This role requires technical expertise across Azure workloads, specifically with AI, Foundry, application services, Power Platform Fusion Development, and GitHub Copilot, and a passion for helping enterprise customers solve complex challenges and accelerate their digital transformation.. This Cloud Solution Architect will work with the customer’s architects, developers and IT staff to build new AI\-infused applications hosted on Azure, modernize existing Azure applications, or migrate applications to Azure and enhance them with AI.
Microsoft is on a mission to empower every person and every organization on the planet to achieve more. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day.
Growth mindset encourages each of us to lean in and learn what matters most to our customers, to create the foundational knowledge that enables us to make customer\-first decisions in everything we do. In doing so, we create life\-changing innovations that impact billions of lives around the world. You can help us achieve our mission.
Responsibilities
Business Impact
- Delivers solutions in line with company methodologies (e.g., product offerings such as value\-based deliverables \[VBDs], advice, training, technical validation), ensuring proven practices and patterns are followed to prepare complex customers for operational readiness and achievement of their business goals and targets. Leveraging knowledge of change management proven practices and/or involving the change management team, proactively helps the customer deploy for long\-term organizational adoption to increase customer satisfaction and drive consumption/usage. Guides complex customers/partners towards a well\-architected (e.g., secure, resilient, artificial intelligence \[AI]\-enabled), and cost\- and performance\-optimized solution to increase retention and expansion opportunities. Articulates the value of Unified and supports sellers, partnering with account teams to build consumption plans aligned with appropriate services. Provides feedback to Unified Delivery Team on VBDs to refine and further develop content.
- Proactively identifies and anticipates new cross\-solution opportunities for Consumption, Usage \& Unified expansion (especially Enhanced Solutions) at scale based on business value to customer/partner and clear understanding of the Microsoft value proposition for supported platforms to empower cloud success, foster and strengthen security and resiliency, and drive AI innovation. Strategically consults with, actively listens to, and respectfully challenges customers/partners, building trust to then advocate for alternative architectures/solutions/approaches that shape and/or enhance customer requirements. Identifies, anticipates, and evaluates industry trends (e.g., customer industry verticals, information technology \[IT] industry), gathers customer/partner insights (e.g., feedback around technical preferences, environments, business needs, competitive landscape), and maps both existing and novel architecture and digital transformation solutions to customer/partner business outcomes. Proactively anticipates and captures opportunities in appropriate systems, processes, and tools, working collaboratively across the organization to execute on opportunities aligned with Microsoft's Customer Engagement Model.
- Anticipates, identifies, escalates, and mitigates blockers using appropriate tools and processes to accelerate solution deployment, value realization and usage/consumption for complex customers/scenarios. Proactively applies broad business, technical, industry, and/or enterprise knowledge to architecture or support projects to meet business and information technology (IT) requirements and resolve identified constraints.
- Operates according to required operational excellence and proven practice standards throughout all sales stages/activities/tools of record (e.g., pipeline updates, time tracking). Orchestrates and collaborates across Microsoft and customer/partner teams through on\-strategy delivery to achieve customer/partner objectives and increase customer/partner satisfaction. Proactively anticipates and manages business and technical risks, adapts methodology and applies governance principles to identify, communicate, and minimize business and technical risks. Executes work in compliance with industry and Microsoft guidelines and procedures. Continuously prioritizes among competing demands in their work and identifies where impact occurs with customers, ensuring alignment with business priorities and goals.
Customer Centricity
- Proactively identifies and/or translates customer/partner problems into industry solutions aligned with Microsoft product and platform strategy, creates or improves an existing business model, and explains why and/or how they meet customer/partner outcomes and return on investment (ROI) goals (e.g., via proof of concept, minimally viable product \[MVP], rapid prototype) relative to competitive offerings. Proactively helps the customer/partner accelerate their adoption and use of Microsoft product/platform strategy\-aligned (cross\-solution area) solutions. Builds relationships with, and provides direction to technical decision makers (TDMs) up to the C\-suite level, and builds the bridge between TDMs and business decision makers (BDMs). Leads and elevates interactions as needed with customers/partners' Chief Information Office (CIO), Chief Information Security Officer (CISO), and other C\-level (CXO) roles to bridge understanding of security, compliance, operational and risk requirements across BDMs, TDMs, CIO and CISO teams, appropriately engaging additional subject matter experts when deeper expertise is required.
- Proactively acts as the voice of the customer/partner, sharing ideas, feedback, insights, success stories and strategic/technical input with Engineering teams, Product Offerings teams and internal communities leveraging relevant insights from feedback tools and systems. Identifies and aggregates patterns of feedback across customers/partners/territories/industries, and leverages them with relevant industry perspective to develop strategic and actionable insights. Presents business cases to program managers to advocate for and influence product roadmaps, decision making, and bug fix prioritization, and own and drive initiatives as appropriate.
- Drives self and guides other team members to focus on customer/partner experience through efficient delivery and ensuring a seamless and connected customer experience. Drives the realization of customer/partner conditions of success by leveraging an understanding of customer goals. Anticipates, addresses, and leads customer confidence calls to resolve customer/partner dissatisfaction and unmet needs, and creates and executes strategies to improve customer experience, value realization, and acceleration of transformation.
Partner Specialization
- Identifies and prioritizes opportunities aligned with revenue goals and orchestrates the growth of the solution utilization pipeline with partners. Provides support to partner and sales teams by bringing clarity to opportunities through proof\-of\-concept development and technical pre\-sales engagement.
- Understands solution area\-specific market opportunities (e.g., competitor insights) and collaborates with Global Partner Solutions (GPS) stakeholders to lead and execute initiatives that translate opportunities into actionable plans. Proactively guides and supports partners in developing repeatable offerings, practices, products, and solutions, and advises partners through initial strategic customer implementations.
Technical Leadership
- Leverages market insights and demand signals to assist leadership in identifying relevant areas in which to drive up\-skilling and/or accreditations based on demand. Role models technical readiness, both depth\-aligned to solution area priorities and breadth\-aligned to Customer Success Unit (CSU)/corporate initiatives (e.g., security, resilience, AI), and influences team to drive their own technical readiness. Acts as a mentor, leading readiness and upskilling activities in the team/organization by educating colleagues on technical and non\-technical concepts and sharing proven practices.
- Demonstrates deep industry knowledge and drives recognition for Microsoft solutions by leading presentations and engagements with external and internal audiences (e.g., Tech Connect, Build, Ignite) Contributes to and collaborates on intellectual property (IP) and proactively identifies patterns where no IP exists (e.g., CoPilot and AI scenarios) to help build scalable and repeatable models. Participates in and leads external technical and non\-technical community events (e.g., conferences, seminars, technical meetups, webcasts, blogs, hackathons) that elevate the Microsoft brand and shares learnings across internal teams.
- Identifies and anticipates gaps through delivery, communicates those gaps to and influences relevant team members and internal/external stakeholders, and connects gaps and patterns across business and technology areas that drive changes and improvements to products, IP (both existing and new), technologies, and/or processes/practices that enable solutions to scale across customers. Develops and contributes to modifications of Microsoft's structured frameworks and methodologies. Proactively provides thought leadership and innovation to customers/partners and internal communities at the worldwide level.
Core Responsibilities:
- Build trusted relationships with IT executives and business leaders to shape their Cloud and AI strategy, acting as a technical advisor and champion for customer success.
- Lead and coordinate across Microsoft, partner, and customer technical teams to manage dependencies, technical risks, and delivery milestones across complex engagements.
- Lead architectural design sessions and guide the implementation of secure, scalable, and resilient solutions using Microsoft best practices and frameworks such as CAF and WAF.
- Drive technical excellence across Azure workloads—particularly AI, Foundry application services, and GitHub Copilot— along with Power Platform Fusion Development \- ensuring mission\-critical workloads are optimized for performance, security, and production\-scale AI readiness.
- Align technical delivery to customer success plans and consumption priorities, ensuring solutions deliver measurable business value and long\-term platform adoption.
- Accelerate Azure consumption and customer outcomes by developing repeatable intellectual property (IP), resolving technical blockers, and providing delivery oversight for key engagements.
- Collaborate with internal teams and partners to design impactful delivery proposals and support execution.
- Translate complex technical concepts into clear business outcomes and executive\-level messaging for senior stakeholders.
- Contribute to Microsoft’s technical community by mentoring peers, sharing insights, and serving as a spokesperson in internal and external forums.
- Maintain advanced certifications and deep technical expertise across priority workloads such as Azure AI Foundry, GitHub, App Services, and Power Platform.
- Inspire customer innovation by helping customers adopt AI at scale and guiding them through their transformation journey.
- Demonstrate a growth mindset by continuously developing technical and professional skills and contributing to a culture of learning and excellence.
- Embody our culture and values
Qualifications
Required/minimum qualifications:* Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 4\+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting
+ OR equivalent experience.
Other Requirements:
Security Clearance Requirements: Candidates must be able to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
- The successful candidate must have an active U.S. Government Top Secret Security Clearance. Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. Failure to maintain or obtain the appropriate clearance and/or customer screening requirements may result in employment action up to and including termination.
- . Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. Failure to maintain or obtain the appropriate clearance and/or customer screening requirements may result in employment action up to and including termination.
- Clearance Verification: This position requires successful verification of the stated security clearance to meet federal government customer requirements. You will be asked to provide clearance verification information prior to an offer of employment.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- This position is not eligible for visa sponsorship. Candidates must have authorization to work in the United States that does not now or in the future require employer sponsorship.
- Citizenship \& Citizenship Verification: This position requires verification of U.S. citizenship due to citizenship\-based legal restrictions. Specifically, this position supports United States federal, state, and/or local United States government agency customer and is subject to certain citizenship\-based restrictions where required or permitted by applicable law. To meet this legal requirement, citizenship will be verified via a valid passport, or other approved documents, or verified US government Clearance
Additional or preferred qualifications:* Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, or related field AND 8\+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting
+ OR Master's Degree in Computer Science, Information Technology, Engineering, Business, or related field AND 8\+ years experience in cloud/infrastructure technologies, technology solutions, practice development, architecture, and/or consulting
+ OR equivalent experience.
- 4\+ years experience working in a customer\-facing role (e.g., internal and/or external).
- 4\+ years experience leading technical projects.
- Comfort and actively uses code/script generation tools like GitHub Copilot, Claude, Opus, Codex
- Competitive Landscape: Knowledge of enterprise public cloud platforms and related industry/marketplace
- Technical Certification in Cloud (e.g., Azure, Amazon Web Services, Google, security certifications).
Cloud Solution Architecture IC4 \- The typical base pay range for this role across the U.S. is USD $106,400 \- $203,600 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $137,600 \- $222,600 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us\-corporate\-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
Salary Context
This $106K-$222K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Microsoft, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $106K to $222K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Microsoft AI Hiring
Microsoft has 49 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Product Manager, Data Scientist. Positions span Redmond, WA, US, San Francisco, CA, US, Washington, DC, US. Compensation range: $159K - $331K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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