Description
Lead Engineer / Founding Engineer
Team: Engineering
Location: Delhi
Commitment: Full Time
Workplace Type: onsite
About Us
At Turgon, we believe there is a massive opportunity to reimagine how IT services are delivered by leveraging a combination of AI agents and humans to build, integrate and run the enterprise stack. AI agents that understand your existing infrastructure, processes and data and can rapidly add new business logic, generate new integrations on the fly, and root cause issues instantly. That’s a $1.5T opportunity!We are a startup based in San Francisco and New Delhi, founded by serial entrepreneurs. With a growing office in South Delhi, we’re assembling a core leadership team to drive architecture, development and delivery across cloud infrastructure, full-stack web and LLM-powered back ends.
Turgon is funded by 3 incredible investors from Silicon Valley and has been one of the most closely watched companies in the US AI innovation market, quoted by top VCs as one of the top 3 enterprise companies in the Valley.
About the Role
We are looking for a lead / founding engineer to help us rapidly scale our AI agents, productize our flows and deliver integration and data solutions to our customers. With a list of marquee customers such as Revlon, McCarthy Tires, Royal Orchid Hotels as well as an exploding demand for our AI-led services, we see this role as being pivotal to our growth.
This is a great opportunity for an entrepreneurial engineer who wants to be at the cutting edge of AI agentic frameworks to work alongside repeat founders, build out the engineering organization and drive incredible impact.
Core Responsibilities
- Lead, mentor and grow a team of AI engineers, Data engineers, DevOps and Full-Stack engineers.
- Architect, build and deploy end-to-end solutions spanning:
- > Full-stack applications (Next.js, React, TypeScript, server-side rendering, APIs)
- > LLM services (LangChain, LangGraph, Hugging Face integrations, model deployment)
- > Cloud infrastructure (AWS/Azure/GCP IaC, CI/CD, monitoring, security)
- Hands-on implementation to bootstrap new projects, troubleshoot critical issues and optimize performance
- Collaborate with the CTO and CEO to align architecture with business goals
- Be on top of the latest research and developments in agentic frameworks. Interface with (and learn from) our AI advisors from OpenAI, Together, NYU etc.
- Recruit, interview and onboard top engineering talent
Must-Have Qualifications
- 5+ years of hands-on experience across DevOps, Full-Stack and LLM-focused back-ends
- Expert in at least one public cloud (AWS, Azure, GCP); comfortable designing IaC (Terraform, CloudFormation) and CI/CD pipelines
- Strong Python skills; hands-on with LangChain, LangGraph (including Multi-Agent Orchestration) and Hugging Face Transformer libraries
- Experience deploying and serving ML/LLM models (Docker, Kubernetes, serverless)
- Solid understanding of data pipelines (SQL/NoSQL) and observability tools
- Excellent communication, planning and stakeholder-management abilities
Nice-to-Have Skills
- Prior startup or founding-team experience
- TensorFlow, PyTorch or other ML framework expertise
- Familiarity with vector databases (Pinecone, Weaviate) and MLOps tools (MLflow, TFX)
- Experience/Familiarity with some Enterprise Software (Snowflake, Data Bricks, any ERP, CRM, Reporting and Analytics etc) or Data Engineering (Enterprise Data Pipelines, Integrations etc)
Education & Certification
- We don’t actually care about qualifications as long as you are a rockstar engineer who wants to keep learning and make a massive impact.
What We Offer
- A values aligned culture: always learning mindset, collaborative environment and an entrepreneurial approach to getting things done
- Competitive, flexible salary based on experience
- Equity via ESOPs
- Leadership role shaping AI/LLM services at enterprise scale
- Collaborative, high-energy startup culture in South Delhi and San Francisco
- Access to top AI researchers worldwide to drive innovation and continuous learning
- Flexible work-from-home days balanced with on-site collaboration
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