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About This Role
Overview:
Location: Remote (U.S.\-Based)Employment Type: Contract
Are you ready to shape the future of AI infrastructure? Trissential is partnering with an innovative client to find a Senior Software Engineer who thrives at the intersection of large\-scale distributed systems and cutting\-edge AI. This is your opportunity to build the backbone of next\-generation AI platforms—where models, agents, and real\-time intelligence come together at scale.
What’s in It for You?* High\-Impact Work – Build the core runtimes powering AI models and autonomous agents across hybrid cloud environments
- Cutting\-Edge Tech Stack – Work with Kubernetes, LLMs, RAG architectures, and modern AI/ML pipelines
- Platform Ownership – Design and influence scalable infrastructure and runtime architecture
- Collaboration Culture – Partner with product, architecture, and data teams to accelerate AI innovation
- Growth Opportunity – Mentor engineers and lead initiatives that shape future platform capabilities
Your Role \& Responsibilities* Design and build scalable back\-end services supporting AI\-driven, data\-centric applications
- Architect high\-performance runtimes for machine learning models and autonomous agents
- Develop and manage hybrid\-cloud infrastructure (AWS, Azure, GCP) with a multi\-tenant design approach
- Implement observability frameworks (logging, metrics, tracing) to ensure system reliability and performance
- Lead and participate in DevOps, CI/CD, and Agile development processes
- Collaborate with product managers, architects, and engineers to translate complex requirements into robust solutions
- Conduct root cause analysis and troubleshoot complex distributed systems
- Mentor junior engineers and contribute to cross\-functional engineering excellence initiatives
- Optimize inference workloads and implement scalable architectures such as RAG pipelines
- Ensure adherence to coding standards, documentation, and best practices across the SDLC
Skills \& Experience You Should Possess* 5\+ years of software engineering experience building scalable back\-end systems
- Strong programming experience in Python, Go, Java, or similar high\-level languages
- Hands\-on expertise with Kubernetes (4\+ years preferred) and container orchestration
- Experience developing cloud\-native applications in hybrid environments (AWS, Azure, GCP)
- Solid understanding of AI/ML lifecycle, including LLM operations and inference optimization
- Proven experience with distributed systems, scalability, and high\-availability architectures
- Strong knowledge of DevOps practices, CI/CD pipelines, and Agile methodologies
- Experience implementing observability solutions (logs, metrics, tracing)
- Excellent problem\-solving, communication, and time management skills
Bonus Points If You Have:* Experience with RAG architectures and agent\-based AI systems
- Background in healthcare or regulated industry software development
- Familiarity with data warehousing, big data systems, and analytics platforms
- Knowledge of business intelligence tools and modern data ecosystems
- Experience working with open\-source technologies in large\-scale environments
Education \& Certifications You Need:* Bachelor’s Degree in Computer Science, Engineering, or related field (required)
- Master’s Degree in a related field (preferred) Certifications in cloud platforms (AWS, Azure, GCP) are a plus
What We Offer
At Trissential, we prioritize innovation, growth, and collaboration. By joining our client’s team, you’ll work on transformative AI initiatives while being supported by a forward\-thinking environment.
- Competitive Compensation – $75–$85 per hour. Final compensation is determined based on skill alignment, years of experience, and fair, market\-based rates by geography.
- Comprehensive Benefits for you and your dependents – Medical, dental, vision, free tele\-health, HSA with company contribution, life and disability insurance, and 401k with matching
- Paid Time Off – Offers paid time away from work
- Remote Flexibility – Work from anywhere within the U.S
- Career Development – Access to training, certifications, and leadership opportunities
- Innovative Work Environment – Build cutting\-edge AI solutions alongside industry experts
Please Note: This role is only open to candidates authorized to work in the United States
Ready to be part of something exciting?
If you’re passionate about building scalable AI platforms and want to work on transformative technology that impacts real\-world outcomes, this is your opportunity. Apply today and help drive the future of AI with Trissential!
Salary Context
This $156K-$176K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 251 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 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At Expleo Group, 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 $232,000 based on 863 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($166K) sits 28% below the category median. Disclosed range: $156K to $176K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Expleo Group AI Hiring
Expleo Group has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span Rochester, MN, US, Minneapolis, MN, US. Compensation range: $176K - $176K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 median, while Prompt Engineer roles sit at $140,000. 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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