AI Engineer Senior Level

• Design and develop LLM-powered AI agents for enterprise workflow automation.

• Build integrations between AI agents and internal enterprise systems using:

• REST APIs
• SQL databases
• MCP servers
• Tool/function calling

Develop multi-step AI workflows for:

• Document processing
• Data validation
• Exception handling
• Operational automation

Implement:

• Guardrails
• Output validation
• Human-in-the-loop workflows
• Audit trails
• Cost tracking
• Rate limiting

Create reusable AI engineering frameworks including:

• Prompt management
• Evaluation harnesses
• Context orchestration
• Structured output validation

Ensure observability through:

• Logging
• Monitoring
• Decision tracing
• Agent action visibility

Collaborate with business and architecture teams to identify automation opportunities and integrate AI solutions into enterprise platforms.

We are looking for a highly skilled AI Engineer with strong software engineering fundamentals and hands-on experience building production-grade LLM-powered applications and autonomous agents. This role focuses on designing and implementing enterprise AI automation solutions that integrate with internal systems, APIs, databases, and operational workflows.

The ideal candidate should have deep expertise in Python and Java, strong experience with LLM APIs such as OpenAI and Claude, and practical exposure to AI agent orchestration, MCP servers, tool calling, observability, guardrails, and enterprise automation frameworks.

This is not a research-focused role. The client needs someone who can independently build scalable, secure, auditable, and production-ready AI systems for Finance and Operations teams., Core Technical Skills

• 7 10+ years of software engineering experience
• 2+ years of hands-on production experience with LLM/AI applications

• Strong programming expertise in:

• Python
• Java

Experience building enterprise-grade backend services

AI / LLM Skills

• OpenAI / Claude / Anthropic APIs
• Prompt engineering
• Function calling
• Tool calling
• Structured outputs
• Context window management
• Multi-agent workflows
• MCP servers
• AI orchestration frameworks

Enterprise Integration Skills

• REST APIs
• PostgreSQL
• SQL Server
• Enterprise databases
• API orchestration
• Workflow automation

AI Reliability & Governance

• Hallucination mitigation
• Output validation
• AI guardrails
• Audit logging
• Human approval workflows
• Observability
• Cost optimization
• Rate limiting

DevOps / Cloud

• AKS (Azure Kubernetes Service)
• GitHub Actions
• CI/CD pipelines
• Monitoring & observability tools

Nice-to-Have Skills

• RAG pipelines
• Vector databases
• LangChain / LlamaIndex
• Temporal workflows
• AI evaluation frameworks
• Financial services domain experience
• Document intelligence systems
• Enterprise AI governance