Build
Solve meaningful enterprise problems with modern AI technologies while working alongside experienced architects and engineers.
Careers
Build the future of Enterprise AI with us
We're looking for curious builders who thrive on solving complex enterprise challenges through AI engineering, platform thinking, and measurable outcomes.
Why Enterprise Labs
Shape enterprise AI from strategy through production.
Direct access to executives, product owners, and enterprise teams
Room to influence how we design, build, and scale the firm
Learn
Engineering-first culture focused on Continuous learning, ownership, and customer impact.
Lead
Take ownership, expand your expertise, and grow into technical and client leadership.
Openings
Join Enterprise Labs as we build production-grade AI systems for real enterprise environments. We are growing with purpose and looking for engineers who want to solve hard problems, ship reliable software, and help clients turn AI ambition into measurable business capability across operations, data, and enterprise workflows.
If you want a high-trust team where modern AI engineering meets practical enterprise delivery and accelerates your growth, we would be glad to meet you.
The Role
You will design, build, and operate software systems that embed agentic AI into enterprise workflows. That means APIs, databases, tests, deployments, observability, and production support — with Agentic AI as a core engineering specialty, not a shortcut around fundamentals.
Beyond strong engineering discipline, we value speed of learning and clarity of execution. You will use AI-assisted tools to prototype ideas, test feasibility, and convert promising concepts into production systems only when they prove business value, technical quality, and a credible path to enterprise adoption.
Responsibilities
- Design, implement, and maintain scalable, robust agentic AI systems that meet performance, cost, reliability, governance, and latency targets
- Build and maintain production backend services and APIs that support enterprise AI applications
- Implement unit, integration, and end-to-end testing for AI systems, including evaluation frameworks, production monitoring, and quality controls
- Participate in code reviews and strengthen engineering standards for production-grade AI delivery
- Use AI-assisted development tools to prototype concepts quickly, validate feasibility, demonstrate value, and iterate toward reliable implementations
- Identify practical agentic AI opportunities for clients and guide teams on architecture, implementation, and adoption
Requirements
- Minimum 3 years of software engineering experience building production-ready systems, with exposure to ML, AI, data engineering, or cloud platforms
- Python experience is required. Experience with additional modern programming languages is welcome
- Experience with LLMs, prompt engineering, RAG architectures, and agentic workflow frameworks such as LangChain, LangGraph, Semantic Kernel, or comparable tools
- Familiarity with vector databases such as Pinecone, Weaviate, Qdrant, pgvector, or adjacent NoSQL technologies
- Ability to explain technical concepts clearly to both technical teams and non-technical business stakeholders
- Familiarity with cloud platforms such as Azure, AWS, or GCP
- Ability to adapt quickly as requirements, models, and AI tooling evolve
- Familiarity with frontend technologies such as React is a plus
What We Value
We believe strong AI systems come from thoughtful collaboration. We look for engineers who contribute ideas, challenge assumptions, and raise the quality of the work around them. If you value clear thinking, direct feedback, practical execution, and continuous improvement, you will feel right at home on our team here.
If you do not match every requirement, we still want to hear from you. We value strong fundamentals, fast learning, engineering judgment, and the discipline to build reliable systems more than a perfect checklist.