Lead Application Developer - Agentic AI
Role details
Job location
Tech stack
Requirements
Proficiency in Java & Angular or Python (with experience in TypeScript, Go a plus).
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Solid understanding of AWS architecture and services-deployment, monitoring, security, and cost optimization.
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Familiarity with agentic or LLM frameworks such as Strands, CrewAI, LangGraph, Agent Core, or similar.
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Experience with retrieval systems, vector databases, embeddings, and orchestration frameworks.
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Strong grounding in secure API design, data modeling, and CI/CD automation.
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Proven record of writing clean, testable, production-grade code.
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Experience designing tool/function-calling integrations and Model Context Protocol (MCP) servers and connectors.
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Strong prompt and context engineering, including agent memory, state, and session/context management.
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Experience with agent and LLM evaluation, guardrails, and safety controls-hallucination mitigation, content filtering, and human-in-the-loop oversight.
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Hands-on experience with foundation models via Amazon Bedrock (e.g., Anthropic Claude), including model selection and prompt/parameter tuning for latency and cost.
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Familiarity with multi-agent orchestration and workflow design-planning, task decomposition, routing, tool use, and error handling.
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Experience with containerization and orchestration (Docker, Kubernetes) for deploying scalable, resilient services.
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Knowledge of Terraform for IaC deployments. Hands-on experience with Terraform is a plus.
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OpenTelemetry for Dynatrace and Observability
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Experience with agent performance tuning and cost optimization.
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Experience with time-boxed A2A and Swarm/Crew Agentic solutions
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Deploying large language models on-prem
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Experience with fine-tuning LLMs - nice to have
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Mindset: Deep curiosity, bias toward execution, and respect for precision and reliability.
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Financial services experience preferred but not required.