AI Application Engineer

Simple Technology Solutions•Washington, DC

21h•Remote

About The Position

Simple Technology Solutions (STS) is seeking an AI Application Engineer to build the software that powers its AI solutions for Federal Government clients. The role develops agents, retrieval pipelines, APIs, and user-facing features that turn customer requirements into working applications. The engineer works test-first from use cases, mockups, and specifications, using Claude Code and shared team agents and skills to deliver high-quality software. Projects may use STS's OpenCORA module architecture or, when required by a client, AWS-native services such as Amazon Bedrock, Lambda, and API Gateway. Success is measured by a steady flow of small, tested, reviewable pull requests linked to Jira cards and regular delivery to users. The engineer collaborates with analysts, technical leads, quality engineers, teammates, and federal clients; contributes to backlog planning and reviews; instruments and secures applications; and supports releases across DEV, TST, STG, and PRD. This is a remote position with occasional travel to client sites and STS events. Candidates in the DC Metro region and remote candidates living in a qualified HUBZone are preferred. U.S. citizenship and the ability to obtain and maintain a Public Trust clearance are required.

Requirements

U.S. citizenship and ability to obtain and maintain a Public Trust clearance.
Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent professional experience in addition to the stated minimum experience.
At least 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, experience 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, including Lambda, API Gateway, DynamoDB, S3, IAM, and 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 approach that favors small, shippable increments over large, perfect ones.
Takes requirements seriously and constructively challenges unclear use cases or specifications.
Self-directed and comfortable owning outcomes on a small, senior team and contributing 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 communication with federal clients and teammates; strong writing and documentation habits.
Bias toward fast delivery and early user feedback over conservative gating, with an ability to learn quickly from failure.
AWS Certified Developer – Associate or AWS Certified Solutions Architect – Associate, and Claude Certified Developer – Foundations (CCDV-F), to be earned within 12 months of hire.

Nice To Haves

AWS Developer or Solutions Architect certification at the Associate level preferred at hire.
AWS Certified AI Practitioner.
AWS Certified Generative AI Developer – Professional.
Claude Certified Architect – Foundations (CCAR-F).
CompTIA Security+.
Residence in the DC Metro region within driving distance of quarterly in-person team events.
Residence in a qualified HUBZone for remote candidates.

Responsibilities

Build and ship generative AI application features, including retrieval-augmented generation, tool-using agents, prompt pipelines, APIs, and user interfaces.
Use test-driven development based on use cases and specifications, writing unit and integration tests before application code and ensuring tests pass before opening pull requests.
Develop business-functionality modules on the OpenCORA module architecture when a project uses it.
Build with AWS-native generative AI and application services when required, including Amazon Bedrock, Bedrock Agents and Knowledge Bases, Lambda, API Gateway, DynamoDB, and S3.
Use Claude Code and shared team agents and skills as the primary development workflow, and contribute improvements to them.
Maintain an audit trail from requirements through Jira cards to GitHub pull requests, with small, reviewable commits tied to cards.
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 to measure, debug, and improve AI behavior.
Review teammates' pull requests, pair with the quality engineer on end-to-end test coverage, and support releases through DEV, TST, STG, and PRD.
Apply secure coding practices appropriate to federal workloads, including secrets handling, input validation, and least-privilege access.