Senior AI Developer Agentic AI

American IT Systems • Plano, TX

1d • Onsite

About The Position

Hands on engineering ownership for enterprise grade AI agents and intelligent workflows.

Requirements

• Demonstrated experience delivering LLM or agent based capabilities beyond prototypes, with evidence of quality evaluation, monitoring, security, and operational support.

Responsibilities

• Design and implement bounded single agent and multi agent workflows using planning, tool calling, state management, human in the loop approvals, memory, and retrieval where each pattern adds measurable value.
• Build agent orchestration with LangGraph or an equivalent framework, including resumable execution, checkpointing, idempotency, timeout handling, loop prevention, and deterministic recovery paths.
• Develop secure tools and enterprise connectors using APIs, events, and Model Context Protocol (MCP), with typed schemas, authorization checks, validation, retries, and safe failure behavior.
• Implement context engineering, structured outputs, prompt and configuration versioning, model selection, and routing patterns that balance quality, latency, reliability, and cost.
• Create reusable agent modules, reference implementations, and integration patterns that can be adopted across multiple business domains.
• Build and optimize retrieval augmented generation (RAG) pipelines using vector, keyword, hybrid, or graph retrieval; implement metadata filtering, grounding, citations, and relevance controls.
• Engineer ingestion and indexing pipelines for structured and unstructured enterprise content, including parsing, chunking, enrichment, embedding, access control, freshness, and deletion handling.
• Select and implement appropriate conversational, episodic, and long term memory patterns while enforcing privacy, retention, tenant isolation, and data minimization requirements.
• Define acceptance criteria and build offline and online evaluation suites using representative datasets, golden traces, automated graders, human review, and regression gates.
• Measure task success, answer groundedness, tool call accuracy, policy compliance, latency, token consumption, cost, and failure patterns; use evidence to drive iterative improvements.
• Implement safeguards for prompt injection, sensitive data, unsafe output, unauthorized tool use, excessive autonomy, and model or dependency failure, aligned with enterprise Responsible AI and security standards.
• Instrument agent workflows with logs, metrics, traces, model and tool spans, feedback signals, and dashboards to support debugging, auditability, and production operations.
• Develop scalable Python services and APIs using FastAPI, Pydantic, asyncio, and sounddistributed systems patterns; integrate with enterprise applications, data services, and event platforms.
• Package and deploy services using containers, Kubernetes, CI/CD, infrastructure as code, and cloud native security controls; contribute to performance, capacity, and reliability engineering.
• Apply production resilience patterns including rate limiting, caching, retries, circuit breakers, fallbacks, concurrency controls, dead letter handling, and graceful degradation.
• Partner with product, domain, platform, security, architecture, SRE, data, and application teams to clarify workflows, assess trade offs, deliver integrations, and drive adoption.
• Lead code and design reviews, improve engineering standards, investigate complex production issues, document reusable patterns, and mentor other engineers without losing hands on ownership.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed