Bachelor's degree in Computer Science, Software Engineering, or related field required.
8+ years of software development experience, including 2+ years with large language model APIs.
Strong proficiency in Python and TypeScript, with modern frameworks for APIs and web front ends.
Experience with test-driven development and continuous integration in AWS environments.
Hands-on experience with Amazon Bedrock and core AWS services (Lambda, API Gateway, etc.).
Familiarity with AI coding assistants and agentic coding tools.
Ability to communicate clearly with federal clients and document processes effectively.
Responsibilities
Build and ship generative AI application features and user interfaces.
Practice test-driven development, ensuring tests pass before pull requests.
Develop on the OpenCORA module architecture for business functionality.
Utilize AWS-native generative AI services when required by clients.
Contribute improvements to shared agents and skills within the team.
Maintain a clean audit trail from requirements to GitHub pull requests.
Participate in backlog grooming and raise requirement gaps early with the team.
Benefits
Comprehensive health, dental, and vision insurance plans.
Professional development and training opportunities.
Performance-based incentives.
401(k) retirement savings plan.
Work from home stipend.
Unlimited PTO and paid holidays.
Flexible work schedule.
Professional development budget for training and certifications.
Full Job Description
AI Application Engineer
Quick Position Overview:
US Citizenship and the ability to obtain and maintain a Public Trust clearance are required
Bachelor's Degree is required
Minimum of 8 years' position related experience is required
AWS Developer or Solutions Architect certification (Associate) preferred for hire; the AWS and Anthropic Claude certifications listed under Required Certifications must be earned within 12 months of hire
Remote position with occasional travel to client sites and STS events
Candidates living in the DC Metro region (within driving distance for quarterly in-person team events) are strongly preferred; STS is a HUBZone company, so residence in a HUBZone is favored for remote candidates
The Role:
The AI Application Engineer builds the software at the heart of STS AI solutions: the agents, retrieval pipelines, APIs, and user-facing features that turn a federal customer's requirements into a working application. You work test-first from the project's requirements trio (use cases, mockups, specifications), using Claude Code and STS's shared agents and skills to move quickly while keeping quality high. Success looks like a steady stream of small, tested, reviewable pull requests that trace back to Jira cards and ship to real users every week. When a client requires AWS-native tooling instead of STS's standard toolchain, you are equally productive building on Amazon Bedrock, Lambda, and API Gateway.
The AI Application Engineer at STS will:
Build and ship generative AI application features, including retrieval-augmented generation, tool-using agents, prompt pipelines, and the APIs and user interfaces that expose them.
Practice test-driven development from the requirements trio, writing unit and integration tests from use cases and specifications before application code and ensuring tests pass before opening a pull request.
Develop on the OpenCORA module architecture when the project uses it, building business-functionality modules on the core chassis and following its conventions.
Build on AWS-native generative AI services, including Amazon Bedrock, Bedrock Agents and Knowledge Bases, Lambda, API Gateway, DynamoDB, and S3, when a client requires AWS services in place of STS's standard toolchain.
Use Claude Code and the team's shared agents and skills as the primary development workflow, and contribute improvements to those agents and skills back to the team.
Maintain a clean audit trail from requirements to Jira cards to GitHub pull requests, and keep commits small, reviewable, and tied to a card.
Participate in backlog grooming, estimate and break down work, and raise requirement gaps early with the business analyst and tech lead.
Instrument applications with logging, tracing, and evaluation hooks so that AI behavior can be measured, debugged, and improved in each environment.
Review teammates' pull requests, pair with the quality engineer on end-to-end test coverage, and support release activities through DEV, TST, STG, and PRD.
Apply secure coding practices appropriate to federal workloads, including secrets handling, input validation, and least-privilege access to data and services.
Education and Experience:
Required
Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent professional experience in addition to the minimum below
Minimum of 8 years of professional software development experience building production web or cloud applications, including at least 2 years building applications on large language model APIs
Demonstrated experience delivering with test-driven development and continuous integration on a team, and shipping to AWS
Experience using AI coding assistants or agentic coding tools in daily work, ideally including authoring reusable prompts, agents, or skills for others
Strong proficiency in Python and TypeScript, including modern frameworks for APIs and web front ends
Working knowledge of retrieval-augmented generation design, vector stores, embeddings, prompt engineering, and evaluation of LLM outputs
Hands-on experience with Amazon Bedrock and core AWS application services (Lambda, API Gateway, DynamoDB, S3, IAM, CloudWatch)
Fluency with Git and GitHub pull-request workflows, Jira, and CI/CD pipelines
Ability to read Terraform and understand how application code is deployed across DEV, TST, STG, and PRD
Pragmatic builder who prefers small, shippable increments over large, perfect ones
Takes requirements seriously and pushes back constructively when a use case or spec is unclear
Self-directed and comfortable owning outcomes on a small, senior team where everyone contributes across the lifecycle
Curious and current on AI tooling; treats AI assistants as part of the team and holds their output to the same standard as human work
Clear, candid communicator with federal clients and teammates; writes well and documents as a habit
Bias toward fast delivery and early user feedback over conservative gating; learns from failure quickly
Required Certifications (to be earned within 12 months of hire)
