AI Developer

Jobtailor

Virginia (MN)

On-site

USD 140,000 - 190,000

Full time

3 days ago

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Job summary

Jobtailor seeks an experienced AI software engineer to design, develop, and maintain AI agents and generative AI applications using Python. You will craft robust agent workflows, refine prompts, and implement RAG and grounding strategies with multi-tool orchestration.

Responsibilities include testing, evaluating model behavior, collaborating with product owners, and ensuring secure, compliant enterprise AI deployments across cloud environments.

Qualifications

Active security clearance required.
Bachelor's degree or equivalent experience in a related field.
Proven hands-on software development with Python in production.
Experience with AI agents, LLMs, and tool integration.
Strong prompt engineering and system-prompt refinement skills.
Experience building REST APIs and integrating external services.
Familiarity with cloud services and DevOps practices.
Ability to design and evaluate multi-tool agent workflows.
Understanding of prompt injection risks and security best practices.

Responsibilities

Design, develop, test, and maintain AI agents and generative AI applications using Python.
Develop agent workflows that interpret requests, reason across steps, select tools, retrieve information, and generate grounded responses.
Refine system prompts, task instructions, and response formats for reliability.
Implement retrieval-augmented generation and grounding strategies in agent workflows.
Build orchestration logic with state/context management and multi-step execution.
Create automated tests and evaluate AI performance with logs and results.
Collaborate with Product Owners to translate problems into AI use cases and acceptance criteria.

Skills

Python Development

Prompt Engineering

AI Agent Workflows

Boto3

Botocore

RAG

Semantic Search

Docker

SQL

API Development

Education

Bachelor's degree in CS/Engineering

Tools

AWS

LangGraph

LangChain

Oracle AI Vector Search

Azure DevOps

Docker

Kubernetes

Job description

Design, develop, test, and maintain AI agents and generative AI applications using Python
Develop agent workflows that use large language models to interpret user requests, reason across multiple steps, select appropriate tools, retrieve information, and generate grounded responses
Design, test, and iteratively refine system prompts, task instructions, tool-use instructions, few-shot examples, response formats, and other prompt-engineering components
Apply prompt-engineering techniques to improve response accuracy, consistency, grounding, tool selection, adherence to business rules, and overall user experience
Develop agent orchestration logic including state management, context management, tool selection, multi-step execution, retries, exception handling, and recovery
Develop Python application components using boto3, botocore, and other appropriate SDKs and libraries to interact with AI, data, storage, security, and supporting cloud services
Integrate agents with approved tools, APIs, Model Context Protocol (MCP) services, databases, knowledge sources, and enterprise applications
Build and optimize retrieval-augmented generation (RAG) capabilities including query formulation, retrieval logic, context assembly, grounding, semantic search, and use of retrieved information within agent workflows
Implement structured outputs, schema validation, response validation, guardrails, error handling, and other controls required for reliable enterprise AI behavior
Develop reusable Python libraries, utilities, agent components, prompts, and development patterns across multiple AI use cases
Create automated unit, integration, regression, and AI evaluation tests
Analyze model and agent behavior using logs, prompts, responses, tool calls, retrieved context, and downstream results
Compare and evaluate models, prompting approaches, retrieval strategies, and agent designs
Collaborate with functional experts and Product Owners to translate business problems into defined AI use cases, expected behaviours, acceptance criteria, and measurable outcomes
Support demonstrations, user testing, defect resolution, production validation, monitoring, and continuous improvement of deployed AI capabilities
Maintain source code, prompts, technical designs, configuration, evaluation criteria, support documentation, and other AI development artifacts
Participate in code reviews, architecture discussions, backlog refinement, demonstrations, testing, release readiness, and Agile/SAFe delivery activities
Perform other duties as assigned

Requirements

Must possess an active Secret security clearance
Must be a U.S. Citizen
Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Information Systems, Engineering, or a related field; equivalent relevant experience may be considered
3+ years of hands-on software development experience, including strong experience developing production-quality applications and services using Python
Strong Python development skills including object-oriented development, modules/packages, dependency management, exception handling, logging, testing, debugging, and API development
Hands-on experience developing AI agents, agentic workflows, LLM-based applications, or comparable generative AI capabilities
Strong hands-on prompt engineering experience, including development and refinement of system prompts, task instructions, few-shot examples, structured outputs, grounding strategies, tool-use instructions, and context-management approaches
Experience developing applications that interact with large language models through APIs or SDKs
Experience developing agent workflows that use tools, APIs, or MCP-based services, including tool selection, structured inputs and outputs, error handling, and integration of tool results into agent behavior
Hands-on experience using boto3 and botocore to develop applications that interact with cloud services and APIs
Experience with retrieval-augmented generation (RAG), semantic search, embeddings, vector search, or other knowledge-grounded AI techniques
Experience developing REST APIs, consuming APIs, working with JSON, and integrating Python applications with external services
Experience developing automated tests or evaluation methods for AI applications, including assessment of response quality, grounding, tool use, or regression behavior
Experience with Git/source control, code reviews, CI/CD, debugging, logging, and modern software-development practices
Strong troubleshooting skills and ability to diagnose problems across Python code, agent behavior, prompts, model responses, retrieval, tools, APIs, and downstream services
Advanced experience developing agentic AI applications involving multiple tools, multi-step workflows, state management, or complex orchestration
Experience designing and optimizing production prompt libraries, agent instructions, reusable prompt templates, and prompt-evaluation approaches
Experience evaluating and mitigating hallucination, weak grounding, inconsistent responses, poor tool selection, excessive context, and other common LLM application problems
Experience with Amazon Bedrock, foundation-model APIs, or comparable managed generative AI services
Experience with agent-development frameworks such as LangGraph, LangChain, Strands Agents, or comparable orchestration technologies
Experience building RAG applications using embeddings, vector search, semantic retrieval, hybrid retrieval, document ingestion, or reranking
Experience with vector databases or Oracle AI Vector Search is a plus
Experience developing AI capabilities involving case management, knowledge management, help desk support, summarization, classification, recommendation, or workflow assistance
Experience consuming MCP services and integrating MCP tools into AI agent workflows
Understanding of AI application security considerations including prompt injection, inappropriate tool use, excessive agency, sensitive-data exposure, authentication, authorization, and least-privilege access
Working knowledge of SQL and relational databases, particularly Oracle
Experience integrating AI applications with PeopleSoft HCM, PeopleSoft CRM, or other complex enterprise applications is a plus
Experience developing containerized Python applications using Docker and deploying applications into cloud or Kubernetes environments
Familiarity with OCI or deployment of AI applications into Oracle Cloud Infrastructure is a plus
Experience working in Agile or SAFe environments and using Azure DevOps (ADO) or a similar lifecycle-management tool
Experience supporting secured Federal or DoD enterprise systems is preferred
Python, AWS, AI/ML, cloud, or related certification is a plus

Core Competencies

Demonstrates expertise in Python development for AI applications, including prompt engineering, agent workflows, and integration with cloud services. Proficient in developing production-quality applications, automated testing, and optimizing AI capabilities for enhanced user experience.

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