AI Engineer Senior Level

Qualifications

• 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

• 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

• Context window management

• AI orchestration frameworks

• Enterprise Integration Skills

• REST APIs

• PostgreSQL

• SQL Server

• API orchestration

• Workflow automation

• Hallucination mitigation

• Human approval workflows

• Observability

• AKS (Azure Kubernetes Service)

• Vector databases

• LangChain / LlamaIndex

• Temporal workflows

• AI evaluation frameworks

• Financial services domain experience

• Document intelligence systems

• 26 more items(s)

Responsibilities

• This role focuses on designing and implementing enterprise AI automation solutions that integrate with internal systems, APIs, databases, and operational workflows

• The client needs someone who can independently build scalable, secure, auditable, and production-ready AI systems for Finance and Operations teams

• 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

• Structured outputs

• Output validation

• AI guardrails

• Audit logging

• Rate limiting

• Monitoring & observability tools

• 34 more items(s)

More job highlights

Job description

Dice is the leading career destination for tech experts at every stage of their careers.

Our client, Metalight Solutions Inc, is seeking the following.

Apply via Dice today!

AI Engineer Senior Level

Location: New York, NY

Client Domain: Alternative Investment / Financial Services

Team: Back Office Operations & Global Business Finance Technology

Job Overview

We are looking for a highly skille...d 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.

Key Responsibilities

• 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.

Required Skills

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

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