Note: The job is a remote job and is open to candidates in USA. ELLKAY is hiring a Staff Machine Learning Engineer - Agentic AI to architect, build, and deploy production-grade AI/ML and agentic systems on AWS. The role focuses on agentic and foundation model applications, healthcare data standards, secure cloud infrastructure, and evaluation of AI systems.

Responsibilities

• Architect, implement, and deploy end-to-end Agentic AI systems utilizing tool calling, stateful multi-agent collaboration, dynamic task routing, reflection loops, and self-correction workflows using frameworks like LangGraph, AutoGen, CrewAI, or Bedrock Agents
• Design and implement production foundation model applications using advanced prompt engineering, structured output design, function-calling patterns, dynamic tool retrieval, and hallucination mitigation strategies
• Build and optimize vector search and long-term memory solutions using OpenSearch Serverless with k-NN, including HNSW/IVF parameter tuning, hybrid retrieval (lexical + semantic), and multi-stage ranking pipelines (BM25 + dense + re-ranking) for RAG and agent context retrieval
• Develop and deploy Amazon Bedrock and Bedrock Agent solutions leveraging Claude family models, Titan Embeddings v2, and Guardrails for PHI/PII detection while optimizing for provisioned vs. on-demand throughput
• Implement classical ML pipelines including clustering algorithms (HDBSCAN, k-means), confidence score calibration (Platt scaling, isotonic regression), and model evaluation frameworks
• Design and implement systems that work with FHIR R4 resources, HL7 v2 message structures, and USCDI data elements
• Build ontology retrieval and agent tool interfaces against LOINC, SNOMED, and RxNorm terminologies to support clinical decision-making and data normalization
• Ensure HIPAA compliance and implement appropriate security controls for protected health information (PHI) across LLM inputs, tool payloads, and agent memory states
• Build high-performance APIs and agent execution backends using FastAPI and Pydantic v2 with async I/O patterns, robust retry/backoff mechanisms, state management, and structured error handling
• Design and deploy AWS serverless architectures including Lambda (Python + container), API Gateway (REST + HTTP), Step Functions, EventBridge, SQS, and SNS
• Implement container-based workloads for agent microservices on ECS Fargate with auto-scaling policies, service discovery, and Fargate Spot optimization
• Architect data and state solutions using Aurora PostgreSQL Serverless v2, DynamoDB, and S3 with appropriate indexing, partitioning, caching, and lifecycle policies
• Write production-grade Infrastructure as Code using AWS CDK (TypeScript or Python) supporting multi-tenant provisioning and cross-account deployments
• Implement comprehensive observability using AWS X-Ray distributed tracing, CloudWatch metrics/logs/alarms, agent execution trajectory tracing, structured JSON logging, and correlation ID propagation
• Apply security engineering best practices including IAM least-privilege roles for tool executions, KMS envelope encryption, Secrets Manager rotation, JWT validation, tenant isolation via session tags, and OWASP API Top-10 awareness
• Design rigorous evaluation frameworks for foundation models and AI agents, including tool selection precision, execution success rates, benchmark creation, per-class metrics, held-out test sets, label leakage prevention, and statistical significance testing
• Implement prompt and agent strategy versioning, human-in-the-loop evaluation pipelines, and A/B testing frameworks to continuously improve performance

Skills

• Proficiency with Pydantic v2, Pandas/Polars, FastAPI, Boto3, Asyncio, and Agent/LLM frameworks (e.g., LangGraph, AutoGen, LlamaIndex)
• Proven experience designing stateful agents, function/tool calling interfaces, autonomous reasoning loops, structured output generation, and evaluation harnesses
• Production experience with Lambda, API Gateway, Step Functions, EventBridge, SQS, SNS, ECS Fargate, Aurora PostgreSQL, DynamoDB, S3, and AWS CDK
• Practical knowledge of OpenSearch Serverless, k-NN algorithms, hybrid retrieval, and ranking optimization for RAG and agent memory stores
• Experience with scikit-learn, clustering algorithms, and confidence calibration techniques
• Good understanding of IAM, KMS, secrets management, and OWASP security principles
• 10+ years of software engineering experience with at least 3 years focused on production AI/ML and GenAI/Agentic systems
• Proven track record of deploying production ML and agentic applications at scale
• Demonstrated ability to design and implement end-to-end ML and agent evaluation frameworks
• Well versed in AI development leveraging tools such as Codex/Claude Code
• Working knowledge of FHIR R4, HL7 v2, USCDI, LOINC, SNOMED, and RxNorm
• Experience with healthcare data or regulated industries

Benefits

• Medical, Dental, and Vision benefits
• Employer-paid Life and LTD
• 401k w/ matching – once eligibility is met
• Work/life balance
• Paid Volunteer Program
• Flexible working hours
• Generous FTO
• Remote work options
• Employee Discounts
• Parental Leave
• Gym membership / Exercise class stipends
• Working with talented, collaborative, and friendly people who love what they do
• Professional growth within
• Innovation environment
• Free daily lunches on site in HQ
• Hybrid workplace, with flexibility in how employees structure their time between in-office and remote work
• For those who do not live within 40 miles of one of our offices, remote work may be considered for candidates whose skills and experience strongly align with the role

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