AI Engineer - III

We are a passionate group of people focused on making financial services accessible to every Indian through a multi-product platform. Each day, we help millions of customers take charge of their financial journey.

Customer obsession is in our DNA. Every product, every design, every algorithm down to the tiniest detail is executed keeping the customers needs and convenience in mind.

Our people are our greatest strength. Everyone at Groww is driven by ownership, customer-centricity, integrity and the passion to constantly challenge the status quo.

Are you as passionate about defying conventions and creating something extraordinary as we are Lets chat.

Our Vision

Every individual deserves the knowledge, tools, and confidence to make informed financial decisions. At Groww, we are making sure every Indian feels empowered to do so through a cutting-edge multi-product platform offering a variety of financial services.

Our long-term vision is to become the trusted financial partner for millions of Indians.

Our Values:

Our culture enables us to be what we are — Indias fastest-growing financial services company. Everyone at Groww enjoys the autonomy and flexibility to bring their best work to the table, as well as craft a promising career for themselves.

The values that form our foundation are:

• 
  Radical customer centricity
• Ownership-driven culture
• Keeping everything simple
• Long-term thinking
• Complete transparency

Were looking for passionate AI Engineers to build intelligent, scalable, and production-ready AI systems that power impactful user experiences. If you enjoy working on cutting-edge AI/ML technologies, solving complex engineering problems, and shipping real-world AI products, wed love to talk to you.

What Youll Do

• Own and scale Growws AI platform, driving architecture, reliability, safety, and AI-powered financial experiences for 50M+ users
• Design and build Agentic AI systems end-to-end — from architecture to production deployment
• Develop scalable RAG pipelines with retrieval strategies, embeddings, vector databases, and financial data integrations
• Build reliable backend systems for AI workflows, including tool orchestration, multi-agent coordination, caching, and session management
• Ensure AI safety and compliance through guardrails, validation layers, fallback handling, and financial policy adherence
• Improve model performance through prompt engineering, evaluation frameworks, and continuous experimentation
• Monitor and optimize production AI systems for latency, reliability, accuracy, and cost efficiency
• Lead technical discussions, mentor engineers, and drive engineering best practices across the team
• Collaborate closely with product, data science, legal, and compliance teams to deliver high-quality AI solutions at scale

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Requirements

• 5–8 years of experience in AI/ML Engineering or related backend engineering roles
• Strong expertise in Go, Java, or Python with experience building scalable distributed systems and backend platforms
• Hands-on experience with Agentic AI frameworks and orchestration systems including planning, tool execution, retrieval, fallback handling, and multi-agent workflows
• Deep understanding of RAG pipelines — retrieval strategies, embeddings, vector databases, re-ranking, and context management
• Strong knowledge of LLM optimization including prompt engineering, evaluation frameworks, latency optimization, and hallucination reduction
• Experience building reliable AI infrastructure with observability, tracing, logging, quality monitoring, and cost optimization
• Strong fundamentals in system design, scalability, resiliency, and performance engineering
• Proven ownership of production systems from architecture to long-term reliability and scalability
• Ability to mentor engineers, drive technical decisions, and uphold engineering best practices
• Strong execution skills with the ability to operate in fast-paced and ambiguous environments
• Proactive mindset with a focus on identifying and resolving issues before they impact production
• Contributions to open-source AI/LLM tooling or internal AI platforms
• Experience building AI evaluation and red-teaming frameworks
• Understanding of AI safety, prompt injection risks, and adversarial attack mitigation in financial systems