Job Title

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.About the Role We are looking for a Back-end engineer to help us rapidly scale our product and AI agents. 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 a Back-end engineer who wants to be at the cutting edge of AI agentic frameworks to work alongside repeat founders and drive incredible impact.Key ResponsibilitiesDesign and implement scalable backend services powering LLM applications Build data pipelines for ingestion, preprocessing and storage (batch & real-time) Integrate and orchestrate LLM frameworks (LangChain, LangGraph, Hugging Face) via Python Collaborate with DevOps to containerize, monitor and automate deployments (Docker, Kubernetes) Ensure data quality, governance and security in AI workflows Optimize inference latency, throughput and cost across cloud/on-prem environments Troubleshoot production issues and iterate on model performance metricsMust-Have Qualifications 3+ years backend development experience in Python Strong expertise in data engineering: SQL/noSQL, ETL frameworks, data validation Hands-on with LangChain, LangGraph (including Multi-Agent Orchestration) and/or Hugging Face Transformers Experience deploying ML models in production (REST/gRPC APIs, serverless or microservices) Solid understanding of ML lifecycle: training, evaluation, monitoring and retraining Familiarity with cloud platforms (AWS, Azure or GCP) for data storage and compute Excellent problem-solving, communication and code-review practicesNice-to-Have Skills Experience with TensorFlow, PyTorch or JAX for model development Knowledge of MLOps tools (MLflow, Kedro, TFX) and model versioning Background in vector databases and similarity search (Pinecone, Weaviate) Prior work with data labeling, annotation tools or active learning pipelinesEducation & Certification Bachelor’s or Master’s in Computer Science, Data Science, Engineering or equivalent experience Relevant certifications (e.g., TensorFlow Developer, AWS/GCP ML Engineer) a plusWhat 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 Opportunity to work at the cutting edge of AI-driven enterprise services Collaborative, high-energy startup culture in South Delhi and San Francisco Access to top AI researchers worldwide to drive innovation and continuous learning.How to Apply Email your resume and a brief note to with “Back-End LLM Engineer” in the subject line.