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About This Role
Description
We are looking for an experienced and detail-oriented Software Engineer to design, build, and support intelligent, modern applications for a federal government partner at Coforma.
Note: This opening is contingent upon Coforma receiving the award for the underlying contract associated with this project. We will keep you updated on the award status throughout the interview process and will inform you immediately if there are any changes regarding the availability of this position.
Our Software Engineers enjoy tackling complex problems while working with other members of our cross-disciplinary teams to deliver elegant products across a modern technology stack. They are skilled across the stack, building accessible applications that put people first with code that is clean, maintainable, well-documented, and well-tested.
This role combines full-stack web application engineering with hands-on AI and machine learning development, enabling you to deliver both the user-facing systems that serve federal employees and retirees and the AI-powered capabilities that make those systems smarter and more efficient over time.
Join us to build software that makes an impact and implement human-centered solutions that we can be proud to say we worked on together.
If you’re passionate about improving lives through digital products and services, Coforma is a great company for you.
$150,235 to $169,146 Annual Salary + Benefits + Growth Potential
Placement within this range will be based on the competency level of the candidate. An offer will be made at one of the following tiers:
- Tier 1 — $150,235.80: Meets stated qualification and experience requirements. May need guidance and training beyond onboarding to perform the more complex functions of the role.
- Tier 2 — $159,691.20: Experienced and fully competent. Will be able to independently perform key responsibilities of the role once onboarding is completed.
- Tier 3 — $169,146.60: Highly experienced and can perform all responsibilities of the role at a higher level than expected once onboarding is completed.
To honor our company-wide equitable pay system, the posted salary range and corresponding tier salaries are non-negotiable.
This is a US-based remote position open to applicants in the states listed below. Some travel may be required.
To ensure we remain compliant with all state, county, and local employment and tax regulations, applicants must currently reside in one of the following states to be considered for employment with Coforma. This list will be updated periodically as our PeopleOps team works to open up hiring in additional states.* Arizona
- California
- District of Columbia
- Florida
- Georgia
- Idaho
- Illinois
- Maryland
- Massachusetts
- Montana
- Nevada
- New Jersey
- New York
- North Carolina
- Oregon
- South Carolina
- Tennessee
- Texas
- Virginia
- Washington
- Wisconsin
What You’ll Do (Key Responsibilities)
You will be working on building a retirement benefits management system for federal government employees. Key areas this role will be responsible for include:* Application Engineering: + Build modular, responsive web applications using React and/or Vue.js in alignment with accessibility and UX best practices. + Design and implement secure, scalable APIs using TypeScript, ASP.NET Core, or Java (Spring Framework). + Integrate with enterprise systems via SOAP/RESTful APIs with robust error handling. + Implement authentication, authorization, and secure configuration in accordance with client agency security policies. + Optimize database access and performance using SQL Server and Entity Framework Core. + Add observability through structured logging, metrics, and tracing and support incident response with clear runbooks.
- AI and Machine Learning: + Design and implement AI agents and large language model (LLM)-powered applications that automate and enhance retirement data workflows. + Build, evaluate, and maintain machine learning models for classification, prediction, and anomaly detection. + Integrate LLMs into production systems using prompt engineering, retrieval-augmented generation (RAG), and agentic frameworks. + Develop and maintain data pipelines that ingest, validate, and transform large-scale structured and unstructured data. + Apply explainable AI practices appropriate for a regulated, auditable government environment. + Track model performance and manage the machine learning (ML) lifecycle using tools such as MLflow.
- Collaboration and Delivery: + Participate in Agile ceremonies, conduct code reviews, and contribute to release planning and documentation. + Work across technical and policy teams to translate business requirements into reliable, AI-driven solutions. + Uphold software engineering best practices such as version control, CI/CD, testing, and peer review across both application and AI workstreams.
What We're Looking For
The strongest candidates bridge two worlds well: they can reason about a React component and a retrieval pipeline in the same conversation. The ideal engineer will read systems before rewriting them, evaluate models critically, and understand that in a mission-critical retirement system, reliability, security, and explainability matter as much as capability.
Who You Are and What You Know (Knowledge and Experience Requirements)
- Full-time resident of the contiguous United States (must be legally authorized to work in the US now and in the future without sponsorship)
- Ability to pass a Public Trust background check and any applicable background and/or security checks related to project requirements
- Proficiency in React, Vue.js, JavaScript, TypeScript, ASP.NET Core, and Java (Spring Framework)
- Strong SQL skills and experience with SQL Server as well as familiarity with EF Core
- Experience with enterprise integrations including message queues, database RPC, REST, and SOAP APIs
- Understanding of authentication, authorization, and security best practices
- Hands-on experience building or deploying LLM-based solutions (e.g., OpenAI, Anthropic, Azure OpenAI, or open-source models)
- Familiarity with agentic AI patterns (tool use, planning, memory, and multi-step reasoning)
- Experience with RAG pipelines, vector databases, and embedding-based retrieval
- Experience using coding agents such as CoPilot or Claude Code
- Effective prompt engineering and experience evaluating LLM outputs for reliability and correctness
Preferred Qualifications and Experience
- 5+ years of experience building applications with open-source programming languages
- 5+ years of experience working with modern frameworks, libraries, or runtimes
- 5+ years of experience working with APIs and databases of various types
- 5+ years of experience working with infrastructure tools and Infrastructure as Code
- Experience developing software in a remote environment
- Experience working in the digital services, federal government, or federal government contracting industries
Other
- Internet: Will prioritize and maintain access to strong, reliable internet for the remote nature of our work, except when on vacation or holiday.
- Security: Will keep the highest security practices to ensure privacy and security of Coforma and client information, given the nature of our work, even when on vacation.
- Travel Flexibility: On request and with advanced notice, will attend in-person events such as meetings, workshops, and trainings as assigned for projects that require it.
- Brand Representation: Will represent Coforma professionally and sincerely, modeling our Company Values in all interactions.
About Coforma
We believe ethical technology begins with responsible innovation.
We’re a remote-first company that values collaboration, inclusivity, transparency, autonomy with accountability, and ethical design processes to facilitate responsible innovation and collaboration.
Our cross-functional team works closely with each other and with our government, nonprofit, and commercial partners to research, design, and build better products and services. From empowering patients navigating surprise medical bills to streamlining the digital claims process for Veterans, we’re dedicated to improving people’s lives through thoughtful technology products and services. Together.
You can learn more about the work we've done and the impact we've made by viewing our Case Studies and reading our 2025 Impact Report, and following us on LinkedIn.
Equal Opportunity & Inclusive Workplace
Coforma is an Equal Employment Opportunity (EEO) employer. It's our policy to provide equal employment opportunities to all qualified applicants without regard to race, religion, sex, gender, age, disability, military or veteran status, or any other factors protected under federal, state, or local law.
We're committed to ensuring accessibility and equal opportunity and offering reasonable accommodations to those with disabilities. We adhere to the guidelines set forth by the Americans with Disabilities Act and all relevant federal, state, and local laws concerning disability discrimination and accommodation. To request a reasonable accommodation for the application or interview process, please email [email protected].
About Public Trust and Other Background Investigations
Due to the nature of our client and project work, most roles may require a National Agency Check and Inquiries (NACI), Moderate Background Investigation (MBI), Background Investigation (BI) or other relevant investigations as needed. Additional information regarding background evaluations or investigations can be found on the U.S. Office of Personnel Management website (opm.gov).
Salary Context
This $150K-$169K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 198 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Coforma, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($159K) sits 27% below the category median. Disclosed range: $150K to $169K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Coforma AI Hiring
Coforma has 1 open AI role right now. They're hiring across AI Software Engineer. Based in US. Compensation range: $169K - $169K.
Location Context
AI roles in Austin pay a median of $209,100 across 306 tracked positions.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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