Job DescriptionSenior AI DeveloperLocation: New York, United States
Type: Full-time
Department: Technology
Job SummaryWe are seeking a Senior AI Developer to support one of our premier clients-a leading global financial institution-with strong expertise in building intelligent AI agents and components that can reason, plan, and act autonomously. The ideal candidate will have hands-on experience developing scalable multi-agent AI systems using modern orchestration frameworks such as LangChain and LangGraph, integrating agentic workflows end-to-end, and shipping production-grade AI applications.
Responsibilities- Design and develop AI agents and autonomous multi-agent systems using modern agentic frameworks including LangGraph and LangChain, with the ability to architect agent graphs, define node transitions, and manage stateful agent workflows
- Build and orchestrate multi-agent pipelines-including supervisor agents, collaborative agent networks, and hierarchical agent architectures-to solve complex, multi-step financial use cases
- Implement guardrails, reasoning workflows, and ReAct-based patterns within LangChain/LangGraph to improve reliability, decision-making, and agent safety
- Develop memory management (short-term, long-term, episodic) and tool-use capabilities (MCP, LangChain Tools, custom tool integrations) for AI agent systems
- Leverage LangGraph's stateful graph execution model to build resilient, interruptible, and human-in-the-loop agentic workflows
- Integrate LLM-powered agents with external APIs, databases, and enterprise data platforms via LangChain's retrieval, routing, and chain composition primitives
- Partner closely with prompt engineers, data scientists, and platform teams to optimize AI application performance across multi-agent deployments
- Build and maintain scalable Python-based services, APIs, and microservices that serve as agent execution environments and tool backends
- Develop and support AIOps capabilities and CI/CD pipelines for AI agent deployment, versioning, and monitoring (including LangSmith or equivalent observability tooling)
- Work with modern data platforms including Snowflake, Databricks, and Lakehouse architectures as grounding and tool-use data sources for agents
- Ensure AI agent solutions are scalable, secure, observable, and production-ready
Eligibility Requirements- 8+ years of overall software engineering experience, with a strong focus on AI/ML systems in recent years
- Hands-on production experience with LangChain - including chains, agents, tools, retrievers, memory modules, and prompt templates
- Hands-on production experience with LangGraph - including stateful graph construction, conditional edges, checkpointing, human-in-the-loop interrupts, and multi-agent graph topologies
- Demonstrated experience designing and deploying multi-agent systems - including orchestrator/worker patterns, agent-to-agent communication, task delegation, and shared state management
- Experience implementing guardrails, ReAct patterns, and chain-of-thought reasoning within agentic pipelines
- Strong understanding of agent memory architectures (in-context, vector-store-backed, episodic) and tool-use patterns (function calling, MCP, LangChain tool wrappers)
- Familiarity with LangSmith or equivalent observability/tracing platforms for debugging and monitoring agent behaviour in production
- Strong Python engineering skills including async programming, APIs, and microservices
- Experience with AIOps and CI/CD pipeline development for AI agent deployment and lifecycle management
- Hands-on experience with Snowflake, Databricks, and Lakehouse architectures
- Strong understanding of scalable distributed systems and cloud-native application development
- Strong communication and cross-functional collaboration skills
- Nice to Have
- Experience with other agentic frameworks such as AutoGen, CrewAI, or OpenAI Assistants API
- Familiarity with LangGraph Cloud or self-hosted LangGraph Server for agent deployment
- Background in financial services AI applications (risk, compliance, trading, operations)
- Experience with vector databases (Pinecone, Weaviate, pgvector) as long-term memory stores for agents
- Contributions to open-source LangChain/LangGraph ecosystem
In the US, the target base salary for this role is $125,000-$140,000. Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications, and geography. We expect the majority of candidates who are offered roles at our company to fall throughout the range based on these factors
How to Apply- Click "Apply Now" to submit your resume through our career site
- Be sure to include any relevant experience that aligns with the role.
- Qualified candidates will be contacted by a member of our recruitment team for next steps
