Agent Developer

Job Description

Overview Design, build, and operate production-grade AI agents and tools using modern agentic frameworks in Python. You?ll implement complete agentic workflows?planning, reasoning, retrieval, tool calling, evaluation, and observability?on AWS-native infrastructure. The role demands hands-on development skills, strong understanding of agent frameworks, and experience integrating securely with enterprise applications and data systems. Responsibilities Build and operate agentic workflows in Python (3.11+) using LangGraph or LangChain (preferred). Experience with Semantic Kernel, AutoGen, or CrewAI is valuable. Implement tool and function calling flows with schema validation, structured arguments, memory, multi-step planning, and orchestration. Develop retrieval-augmented generation (RAG) and hybrid search pipelines ? ingestion, chunking, embeddings (Bedrock/OpenAI), ranking, query planning, grounding, and caching. Deploy and operate agents on AWS Elastic Kubernetes Service (EKS) or Amazon ECS; manage components like S3, RDS (SQL Server), ElastiCache (Redis), Amazon SQS/SNS, and OpenSearch Serverless. Use AWS Bedrock for model orchestration and custom RAG services for knowledge retrieval; integrate with external systems through API Gateway and secure endpoints. Ensure observability and reliability: tracing, metrics, and structured logs via Datadog and OpenTelemetry; define alert thresholds and dashboards. Integrate with enterprise applications (e.g., SAP, Salesforce, ServiceNow) using APIs with OAuth2/OIDC, retries, and idempotency. Apply security and compliance best practices ? IAM policies, AWS Secrets Manager, content filters, prompt-injection defenses, and audit logging. Collaborate with AI architects, backend engineers, and product teams to optimize agent performance, cost, and user experience. Use existing CI/CD pipelines (GitHub Actions / AWS CodeBuild / CodePipeline) for build, test, and deployment; maintain test coverage with pytest and regression suites . Must Have 4?6 years in AI/ML or backend engineering, including 2+ years building GenAI or agentic solutions. Strong command of Python 3.11+ ? asyncio, typing, packaging, pytest, and profiling. Hands-on experience with LangGraph or LangChain (preferred) for tool orchestration, reasoning, and memory. Experience designing RAG pipelines with vector stores like OpenSearch, pgvector, or Pinecone. Working knowledge of AWS components: EKS, S3, RDS, ElastiCache, SNS/SQS, API Gateway, and Secrets Manager. Proven ability to instrument and monitor services with Datadog, CloudWatch, and OpenTelemetry. Strong grounding in security, rate limiting, circuit breakers, and resilient service design. Clear and structured communication ? design docs, flow diagrams, and code reviews. Good to Have Multi-agent collaboration patterns ? coordinator-worker, task decomposition, human-in-the-loop. Evaluation depth ? regression suites, hallucination detection, grounding and recall scoring. Familiarity with AWS Bedrock, LLM evaluation pipelines (phoenix/arize, promptfoo), or custom guardrail frameworks. Experience building streaming or chat-based agent UIs integrated with reasoning traces. Exposure to DevOps workflows ? Docker, CI/CD use, environment promotion, and release versioning (setup not required).