- Job Type: Full-Time
- Function: Data Science
- Industry: Enterprise
- Post Date: 04/03/2026
- Website: contractpodai.com
- Company Address: 4 Kingdom Street, 5th Floor, London, London, W2 6BD, GB
About ContractPodAi
ContractPodAi®, the leader in contract lifecycle management, streamlines and simplifies processes across the full spectrum of in-house legal teams’ workloads with One Legal Platform.Job Description
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OUR STORY
Leah empowers enterprises to build, orchestrate, and govern intelligent AI agents across legal, procurement, finance, and beyond. Our solution combines advanced AI with deep domain expertise across three core products: Leah Agentic OS, Leah Contract Lifecycle Management (CLM), and Leah Legal. Founded in 2015, Leah automates complex workflows, connects data silos, and drives measurable ROI at scale.
Trusted by over 400 global enterprises and backed by leading investors including Insight Partners and SoftBank, Leah, a ContractPod Technologies Limited company, has been recognized as a CLM Visionary by Gartner for five consecutive years and a Leader in the 2025 IDC MarketScape for AI - Enabled Buy - Side CLM Applications.
Headquartered in London with offices in New York, Glasgow, San Francisco, Toronto, Sydney,
Mumbai, and Pune, we're helping enterprises worldwide build the AI intelligent infrastructure of
the future. Join our team and shape what's next in enterprise AI.
THE OPPORTUNITY
We are hiring an Agentic AI Engineer to build advanced agentic AI systems using the LangChain ecosystem.
This is a core engineering role focused on designing and implementing stateful, context-aware AI agents and long-running reasoning systems. The role is strictly technical and backend-focused, not coordination, PM, or basic chatbot/RAG development.
You will work on building production grade agent workflows with structured state, memory, and tool orchestration using LangChain, LangGraph, and LangSmith.
WHAT YOU WILL DO
- Design and develop advanced agentic systems using Python
- Build multi-step, stateful AI workflows using LangGraph
- Implement structured state and context management across agent lifecycles
- Design memory and persistence strategies for long-running agents
- Build tool-using and reasoning agents with controlled execution flows
- Implement structured outputs, guards, and reliability mechanisms
- Integrate LLMs and external tools/APIs into agent pipelines
- Use LangSmith for tracing, debugging, evaluation, and monitoring
- Optimize reliability, latency, and scalability of agent workflows
- Write clean, modular, production-grade Python code
WHAT YOU WILL NEED
- Strong Python development experience and 4+ years of experience.
- Hands-on experience with:
- LangChain
- LangGraph
- LangSmith
- Experience building stateful agent-based systems (not basic prompt wrappers)
Strong understanding of:
- State management in agent workflows
- Context propagation across multi-step executions
- Structured memory and persistence
- Tool-calling and controlled execution loops
- Strong debugging and backend system design skills
Strongly Preferred:
- Experience designing complex multi-step reasoning systems
- Exposure to modern agent orchestration patterns/frameworks
- Experience with evaluation, observability, and reliability of LLM systems
- Async Python and performance optimization experience
- GitHub or demonstrable agentic AI projects
BENEFITS
• Competitive salary
• Opportunity to work in a fast-moving, high growth SaaS company
• Paid Time off
• Comprehensive Insurance coverage
At Leah we believe in creating a diverse and inclusive workplace where everyone feels heard and valued. We are proud to be an Equal Opportunity Employer. We do not discriminate in employment on the basis of race, color, religion, sex, national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.