Senior Software Engineer - Generative AI

Newtuple Technologies
Pune Division, Maharashtra, India

About the RoleWe are looking for a highly skilled Senior Software Engineer with deep, hands-on experience in Generative AI, large language models (LLMs), and modern ML systems. This is an end-to-end engineering role: you will design, build, and deploy AI-driven systems while working closely with founders, clients, and cross-functional teams.

At Newtuple, engineers work across multiple problem domains, from real-time voice agents to RAG systems, on-prem LLM deployments, workflow automation, and large-scale enterprise AI applications. You’ll take ideas from prototype to production in weeks, not months, and operate in an environment that rewards ownership, speed, and innovation.

A key expectation for this role is comfort with AI-assisted development, including the use of AI coding tools, agents, automated refactoring workflows, and LLM-driven engineering assistance. We want engineers who actively leverage AI to accelerate development.

ResponsibilitiesGenAI Development

  • Design, develop, and deploy GenAI-based applications including RAG systems, retrieval pipelines, LLM-powered workflows, evaluation tools, and production agents.
  • Ability to quickly prototype AI applications as well as develop for production scaleSoftware Engineering
  • Architect and implement high-performance backend systems in Python, Node.js, or similar languages.
  • Build reliable, maintainable microservices, APIs, and full pipelines that support AI features end-to-end.
  • Convert loosely defined ideas and client requirements into production-quality systems through rapid prototyping and iteration.
  • Work across multiple projects and adapt quickly to new domains and technical stacks.

LLMOps & Deployment

  • Implement CI/CD pipelines, model monitoring, evaluation dashboards, and end-to-end model lifecycle workflows.
  • Deploy and scale AI systems on cloud platforms (AWS, GCP, Azure).
  • Optimize compute cost, latency, and performance across both training and inference.

Research & Innovation

  • Stay up to date with the latest advancements in GenAI, multimodal models, vector databases, and agent frameworks.
  • Experiment with and evaluate open-source models such as LLaMA, Mistral, DeepSeek, and others.
  • Explore autonomous AI agents, orchestration frameworks, and emerging tooling that improves developer productivity.

Requirements:

Must-Have Skills

  • 4+ years of full-time software engineering experience, including 1–2 years working directly with LLMs or applied ML.
  • Strong command of Python, ML frameworks (PyTorch/TensorFlow), and LLM tooling (Transformers, LangChain, LlamaIndex, etc.).
  • Hands-on experience building RAG pipelines, using embeddings, vector databases (FAISS, Pinecone, Milvus), or fine-tuning LLMs.
  • Proven experience deploying production-grade AI applications.
  • Solid understanding of algorithms, data structures, system architecture, and API design.
  • Comfort using AI coding assistants and AI agents to accelerate development, including code generation, refactoring, testing, and multi-step reasoning automation.
  • Ability to operate independently in ambiguous environments and convert rough requirements into working solutions.
  • Strong generalist skills: backend engineering, cloud services, data workflows, experimentation, and research.

Good-to-Have

  • Experience with multi-agent systems (OpenAI Agents SDK, Claude Agents SDK, CrewAI, LangGraph, others).
  • Familiarity with multimodal AI (Vision/Audio models).
  • Knowledge of distributed systems and high-performance computing.
  • Experience working in a startup or fast-paced consulting environment.

What We Offer

  • Opportunity to work with a cutting-edge Generative AI company based in Pune.
  • Ownership of key AI initiatives and full-stack responsibility from prototype to production.
  • Direct collaboration with founders and exposure to a wide variety of domains: HRTech, Retail, Surveillance, Finance, Healthcare, and more.
  • A fast-paced environment where experimentation, rapid delivery, and solving real problems for real customers is the norm.
  • Growth paths into Tech Lead, AI Architect, or other roles as the company scales.

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