Job Title : Senior AI Platform Engineer - Agentic AI
Location : Chicago, IL
Client: TCS
Rate: $82/hr on W2
Positions: 2
JD :
Job Description
Senior AI Engineer - Agentic AI Platform
Location
Chicago, IL (Hybrid)
3 days onsite (Tuesday to Thursday)
Remote Monday and Friday
Position Summary
We are seeking a highly skilled Senior AI Engineer to help design and build an enterprise-scale Agentic AI platform that enables multiple business domains to develop, deploy, monitor, and govern autonomous AI agents.
This role goes beyond traditional LLM application development and requires hands-on expertise in agent orchestration, AI platform architecture, model governance, memory management, observability, cost attribution, multi-agent systems, and scalable cloud-native AI solutions.
The ideal candidate will have experience building production-grade AI systems using Azure AI Foundry, LangChain, LangGraph, vector databases, API gateways, and modern AI engineering practices. The individual should be comfortable making architecture decisions, evaluating technology trade-offs, and designing enterprise-ready solutions that support security, scalability, monitoring, and cost control.
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Key Responsibilities
Agentic AI Solution Development
Design and develop sophisticated multi-agent AI systems for enterprise use cases.
Build autonomous and semi-autonomous AI workflows using Agentic AI patterns.
Implement supervisor-worker, sequential, orchestration, choreography, ReAct, Planner-Executor, and Writer-Critic agent architectures.
Develop scalable agent communication and execution frameworks.
Design closed-loop AI workflows with validation, retry, evaluation, and feedback mechanisms.
Enterprise AI Platform Engineering
Build reusable AI platform capabilities consumed by multiple business teams.
Implement enterprise-grade AI governance and operational controls.
Design API-driven AI service architecture with:
o Rate limiting
o Quota management
o Multi-tenant usage tracking
o Cost attribution
o Authentication & authorization
o Audit logging
Enable structured onboarding and lifecycle management of AI agents.
Multi-Agent Orchestration
Design orchestration frameworks where agents communicate through:
o Direct calls
o Event-driven architectures
o Message queues
o Publish-subscribe patterns
Implement choreography and conductor-based execution models.
Evaluate technologies such as Kafka, Azure Durable Functions, Service Bus, and event-driven workflows.
AI Memory & Knowledge Systems
Design short-term and long-term memory architectures.
Implement:
o Vector databases
o Semantic caching
o Conversation memory
o Agent state persistence
o Retrieval-Augmented Generation (RAG)
Develop knowledge orchestration frameworks supporting agent collaboration.
Ontology & Graph-based Intelligence
Work with graph databases and enterprise knowledge models.
Support ontology-driven AI applications.
Build knowledge graphs that enable relationship-based reasoning and signal generation.
Design systems that combine structured, unstructured, and graph-based knowledge sources.
Model Governance & FinOps
Implement AI consumption governance across business domains.
Track:
o Token usage
o Model consumption
o API utilization
o Operational costs
Create chargeback/showback mechanisms for enterprise teams.
Support AI FinOps reporting and capacity planning.
Reliability, Monitoring & Observability
Design observability frameworks for AI applications.
Monitor:
o Agent executions
o Tool usage
o Latency
o Hallucinations
o Failure rates
o Model quality
Create dashboards and operational metrics for enterprise AI workloads.
Responsible AI & Security
Implement:
o Guardrails
o Safety controls
o Prompt protection
o Data masking
o PII protection
o Human-in-the-loop validation
Ensure compliance with enterprise security and governance policies.
Build secure agentic systems handling sensitive business data.
AI Evaluation & Optimization
Develop frameworks for:
o Agent evaluation
o Tool evaluation
o Response quality measurement
o Closed-loop evaluation
o Hallucination detection
Apply advanced AI engineering techniques including:
o Context engineering
o Prompt engineering
o Retrieval optimization
o Agent tuning
o AI system benchmarking
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 91171926
- Position Id: OOJ - 1657-661-1787939314
- Posted 8 hours ago
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