Senior Software Engineer

Senior Software Engineer (Generative AI)

About the Role

We 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.

Responsibilities

AI & ML Development

● Design, develop, and deploy Gen AI-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 scale

Software 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.

MLOps & 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

● 7+ 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 (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.