Interested in this AI Software Engineer role at Credence?
Apply Now →Skills & Technologies
About This Role
Overview
Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700\+ team members, 1,500\+ AI/data experts, and 100\+ prime contracts, we deliver at scale and with purpose.
We’ve been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world\-changing Federal challenges.
Position Summary
Credence has an immediate need for a Senior AI Software Engineer to join our growing AI and Automation practice. In this role, you will serve as a senior technical contributor responsible for designing, developing, and deploying advanced AI\-driven solutions, including generative AI, LLM\-powered applications, and agentic AI systems. You will collaborate with cross\-functional engineering, data, cloud, and stakeholder teams to deliver scalable, secure, and mission\-focused AI capabilities for federal clients, while helping guide technical direction, strengthen engineering practices, and mentor other engineers.
Responsibilities include, but are not limited to the duties listed below
- Generative AI \& LLM Solution Delivery
Lead the design, development, prototyping, and refinement of AI\-powered capabilities using generative AI, large language models, retrieval patterns, prompt/context engineering, and secure API integrations.
- Agentic AI System Development
Own end\-to\-end agentic AI development lifecycles, including model selection, agent design, tool/function calling, orchestration, response synthesis, evaluation, and deployment of reliable AI agents.
- Senior Software Engineering Leadership
Apply strong software engineering principles to design maintainable, testable, and scalable systems; conduct code reviews, establish technical patterns, and leverage AI\-assisted development tools responsibly to accelerate delivery.
- Cross\-Functional Technical Collaboration
Partner with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and mission needs into operational AI and automation solutions.
- Cloud Enablement \& DevSecOps Integration
Design and automate deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud\-native services to support secure, repeatable, and scalable AI delivery.
- Production Monitoring \& Optimization
Monitor AI systems post\-deployment, perform performance tuning, and apply best practices for reliability and scalability.
- Technical Rigor \& Documentation
Write clean, well\-documented code following industry and federal guidelines; support reproducible development.
- Technical Mentorship \& Continuous Improvement
Stay current on emerging AI/ML trends, agentic frameworks, model capabilities, and engineering practices while mentoring team members and contributing to reusable standards, documentation, and technical design reviews.
Requirements What You Bring
- TS/SCI clearances Required (CI poly preferred).
- Bachelor’s or Master’s in Computer Science, AI/ML, or a related field.
- 7\+ years of hands\-on software engineering experience, including significant experience delivering AI/ML, generative AI, or LLM\-powered solutions in production or production\-like environments.
- Experience building generative AI applications, working with LLMs, implementing tool/function calling, and applying model evaluation, prompt/context engineering, or retrieval\-augmented generation approaches.
- Experience designing or implementing agentic AI solutions using frameworks or platforms such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph.
- Strong understanding of leading AI APIs and model platforms such as OpenAI, Anthropic, Gemini, Amazon Bedrock, and Google Vertex AI.
- Proficiency in TypeScript and familiarity with key libraries and frameworks such as Nx, Next.js, Mastra, Vercel AI SDK, Playwright, Jest, and Vite.
- Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured).
- Demonstrated curiosity and practical experimentation with emerging AI technologies, with a strong focus on responsible innovation and measurable mission impact.
- Familiarity with CI/CD pipelines (GitLab CI)
- Experience with VS Code and AI extensions such as Cline and Claude Code.
- Strong communication skills and client\-oriented mindset.
Preferred
- Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact.
- Exposure to adjacent skillsets such as data engineering, data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem.
- Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications.
- Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.
Why This Role Matters
- Real\-World Impact — Your work will support defense and health agencies where AI solutions directly contribute to national security and public well\-being.
- Growth\-Oriented Technical Leadership — Work with technical leaders, shape agentic AI delivery practices, and mentor team members while continuing to deepen your own expertise in advanced AI engineering.
- Culture of Empowerment — You’ll be part of a team that values innovation, trust, collaboration, and mission success.
Salary Range: $155,000 \- $200,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications.
Benefits
- Health Care Plan (Medical, Dental \& Vision)
- Retirement Plan (401k, IRA)
- Life Insurance (Basic, Voluntary \& AD\&D)
- Paid Time Off (Vacation, Sick \& Public Holidays)
- Family Leave (Maternity, Paternity)
- Short Term \& Long Term Disability
- Training \& Development
- Wellness Resources
Salary Context
This $155K-$200K range is below the median for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Credence, 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 $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($177K) sits 19% below the category median. Disclosed range: $155K to $200K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Credence AI Hiring
Credence has 2 open AI roles right now. They're hiring across AI Software Engineer. Positions span Herndon, VA, US, McLean, VA, US. Compensation range: $200K - $200K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.