

Location: Hyderabad, Hybrid, Remote
We’re looking for a Lead Machine Learning Engineer to help us transform the Insurtech space. You’ll build intelligent agents and models that read, reason, and act.
Insurance ops are broken. Underwriters drown in PDFs. Risk clearance is chaos. Emails go in circles. We’ve lived it – and we’re fixing it. Bound AI is building agentic AI workflows that go beyond chat. We orchestrate intelligent agents to handle policy operations end-to-end:
• Risk clearance.
• SOV ingestion.
• Loss run summarization.
• Policy issuance.
• Risk triage.
No hallucinations. No handwaving. Just real-world AI that executes – in production, at scale.
What We’re Looking For
- Deep, hands-on experience in GenAI, LLM fine-tuning, and multi-agent orchestration frameworks (LangChain, DSPy, Haystack, or similar), with a track record of delivering production-ready systems.
- 6+ years of proven experience in Machine Learning and AI engineering, with a strong emphasis on leadership, architecture ownership, and scaling ML systems in real-world environments.
- A solid ML/AI engineering background spanning both foundational modeling (NLP, transformers, RAG) and traditional machine learning approaches.
- Strong Python engineering skills — you write clean, scalable, production-ready code, not just research notebooks.
- A startup mindset — curiosity, speed, resourcefulness, and a relentless focus on shipping solutions that move the needle.
- Proven ability to mentor and guide ML specialists and engineers, fostering technical growth and best practices within a fast-paced team.
- Bonus: Experience in insurance tech or document intelligence (SOVs, Loss Runs, ACORDs) is highly valued.
What You’ll Be Doing
- Own, design, and optimize major architectural components within our AI infrastructure, ensuring scalability, reliability, and performance.
- Lead the development of GenAI agents for real-time decision-making, workflow orchestration, and modular multi-agent systems interacting with APIs, humans, and other agents.
- Design and build foundation-model-based pipelines to read, extract, and reason over complex insurance documents.
- Architect and maintain auto-adaptive, feedback-driven workflows that optimize dynamically based on data quality, operational context, and risk signals.
- Provide hands-on technical leadership across AI/ML projects, ensuring scalable, production-grade code and robust deployments.
- Mentor, coach, and grow a team of ML specialists and engineers, fostering a culture of engineering excellence, continuous learning, and innovation.
- Collaborate closely with product, engineering, and operations leaders to prioritize AI-driven solutions that directly impact our customers’ workflows.
Who We Are
- Bound AI was born inside OIP InsurTech – a 1000+ person global company that powers operations for MGAs and brokers across the U.S.
- We’re backed, battle-tested, and already deployed in the wild. This isn’t “build it and they might come.” The market is here – and we’re scaling fast.

About OIP Insurtech
About
OIP Insurtech streamlines insurance operations and optimizes workflows by combining deep industry knowledge with advanced technology. Established in 2012, OIP InsurTech partners with carriers, MGAs, program managers, and TPAs in the US, Canada, and Europe, especially the UK.
With 1,200 professionals serving over 100 clients, we deliver insurance process automation, custom software development, high-quality underwriting services, and skilled tech staff to augment our clients.
While saving time and money is the immediate win, the real game-changer is giving our clients the freedom to grow their books, run their businesses, and focus on what they love. We’re proud to support them on this journey and make a positive impact on the industry!
Tech stack



Candid answers by the company
Our robotics team has all graduated from our insurance boot camp. They code insurance for a living and bring with them best practices from more than 80 different systems across the insurance ecosystem.
They’ve seen what works for E&S businesses – they’ve built them. And they know what it takes to help your team deliver the better result.
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