Inductiv is a private, applied AI lab and product studio that develops AI-first solutions for enterprises. Our work combines a deep understanding of AI algorithms (including GenAI) with expertise in production systems engineering.

Role Description

We are seeking an experienced AI Engineer to design, build, and deploy end-to-end machine learning systems—with a strong emphasis on generative AI, LLMs, and AI agent architectures. As one of our first AI engineering hires, you’ll work at the intersection of research and production, collaborating closely with AI researchers, backend engineers, and product teams to turn cutting-edge models into reliable, scalable enterprise solutions.

You’ll be responsible for the full lifecycle of AI systems—from prototyping novel agent workflows and fine-tuning LLMs to deploying and monitoring production-grade inference pipelines. If you thrive on bridging the gap between advanced AI concepts and real-world engineering constraints, this role is for you.

Key Responsibilities:

• Design, implement, and maintain scalable ML and GenAI systems, including LLM-powered applications and autonomous AI agents.
• Develop robust pipelines for training, fine-tuning, evaluating, and serving foundation models (e.g., via Hugging Face, vLLM, TGI, or custom frameworks).
• Architect and optimize retrieval-augmented generation (RAG), agent orchestration, tool-use frameworks, and multi-agent collaboration systems.
• Integrate AI components with backend services (APIs, databases, cloud infrastructure) to support end-to-end product functionality.
• Implement observability, monitoring, and evaluation frameworks for AI system performance, latency, cost, and safety.
• Collaborate with data scientists to productionize experimental models and techniques while ensuring reliability, security, and compliance.
• Optimize inference latency, throughput, and cost using techniques like quantization, distillation, caching, and model routing.
• Contribute to MLOps infrastructure—CI/CD for models, versioning (e.g., MLflow, DVC), and A/B testing frameworks.
• Stay current with advancements in LLMs, agentic AI, and responsible AI practices, and assess their applicability to our products.

Qualifications

Required Skills & Experience:

• 3+ years of hands-on experience building and deploying production ML/AI systems.
• Strong proficiency in Python and modern ML/AI tooling (PyTorch, Transformers, LangChain/LlamaIndex, DSPy, or similar).
• Demonstrated experience working with LLMs—including prompt engineering, fine-tuning (SFT, LoRA, QLoRA), and deployment.
• Experience designing and implementing AI agent systems (e.g., ReAct, Plan-and-Execute, PydanticAI, CrewAI or custom agent frameworks).
• Solid understanding of vector databases (e.g., Pinecone, Weaviate, Qdrant) and RAG architectures.
• Familiarity with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
• Experience with model serving frameworks (e.g., Triton, TorchServe, FastAPI-based endpoints).
• Strong software engineering fundamentals: testing, version control (Git), code reviews, and system design.
• Bachelor’s degree in Computer Science, AI, or a related field (or equivalent practical experience). Master’s preferred.

Nice-to-Have (Bonus Skills):

• Experience with multi-modal models or agentic workflows involving vision, speech, or structured reasoning.
• Knowledge of LLM safety, alignment techniques, or evaluation methodologies (e.g., HELM, MT-Bench).
• Contributions to open-source AI projects or a public portfolio of AI/agent demos.
• Familiarity with privacy-preserving ML (e.g., differential privacy, federated learning).
• Experience with graph-based reasoning or knowledge graphs in AI systems.
• Background in distributed systems or high-throughput inference infrastructure.

Why Join Inductiv?

• Work on the frontier of applied generative AI and agentic systems for real enterprise impact.
• Collaborate with a small, elite team of engineers and researchers who value depth, rigor, and craftsmanship.
• Shape the technical direction of AI products from day one—with ownership and autonomy.
• Solve hard problems in AI reliability, scalability, security, and usability.
• Competitive salary, growth opportunities, and a dynamic work environment.

Ready to engineer the next generation of intelligent enterprise systems?
We’re building more than models—we’re building AI that works in the real world. If you’re passionate about turning LLMs and agents into production-grade solutions, we’d love to hear from you.

Saurav Dhungana

Saurav Dhungana is the founder of Inductiv AI Labs, a privacy-first artificial intelligence company developing trustworthy AI systems for enterprise and individual users. With over a decade of experience engineering privacy-first AI systems, Saurav advocates for transparent, accountable artificial intelligence development.

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