AI Engineering Lead

AtFadata, we take pride in our ability to adapt quickly to the ever-changing needs of our market and customers. This means that you, too, should be ready to embrace change as circumstances evolve. If you're excited about a fast-paced, dynamic environment where strategy is set but flexibility to grow with the market remains, then

We have a bold vision: to become the global standard for core software solutions in the insurance industry. Our aim is to achieve this by developing a truly cloud-native solution that can scale limitlessly—and we want you to be part of that journey.

Our values—Trust,Openness,Passion,Innovation, andCare—serve as our guiding compass. They shape how we work every day, our relationships with clients, and the way we collaborate as a team.

We are looking for a highly motivated and experienced AI Engineering Lead to join our growing AI Engineering team. You will play a key role in designing, building, and delivering production-ready AI solutions focused on LLM applications, agentic workflows, AI orchestration, RAG systems, and AI automation.

This is primarily a hands-on engineering role with technical leadership responsibilities. You will help lead one AI Engineering team through technical execution, mentoring, and engineering best practices, while remaining deeply involved in implementation and solution delivery.

You will work closely with Product Managers, Architects and engineering teams to build scalable and reliable AI capabilities that deliver measurable business value in real enterprise environments.

• Design, build, and maintain production-ready AI solutions using modern LLM and agentic AI technologies

• Develop AI workflows, orchestration layers, RAG pipelines, and AI automation capabilities

• Build scalable and maintainable AI services, APIs, and integrations using Python and modern backend engineering practices

• Prototype, iterate, and product ionize AI capabilities in a fast-moving and experimental environment

• Implement prompt engineering, context management, tool usage, and structured AI output strategies

• Develop evaluation, validation, testing, monitoring, and feedback mechanisms to ensure AI reliability and quality in production

• Contribute to AI governance, observability, security, and operational best practices

• Collaborate closely with Architects to align AI solutions with the broader platform architecture and engineering standards

• Work closely with Product Managers and stakeholders to translate business needs into practical AI solutions

• Provide technical leadership, mentoring, and guidance to our AI Engineering team

• Support technical execution alignment, implementation quality, and engineering best practices within the team

• Participate in technical interviews, hiring, and the growth of the AI Engineering capability within the organization

• Stay current with emerging AI technologies, tooling, and engineering practices relevant to enterprise AI development

• Strong software engineering experience with Python and modern backend development practices

• Hands-on experience building production-ready AI/LLM applications and workflows

• Experience with frameworks such as Lang Chain, Lang Graph, or similar AI orchestration technologies

• Experience designing and implementing RAG architectures and vector database integrations

• Practical understanding of AI agents, orchestration patterns, tool calling, and context management

• Experience working with cloud AI platforms, preferably AWS Bedrock

• Strong understanding of AI system reliability, validation, evaluation, monitoring, and governance concepts

• Experience building scalable APIs and integrating AI capabilities into enterprise systems

• Strong problem-solving skills and ability to work effectively in ambiguous and evolving environments

• Excellent communication and collaboration skills with both technical and non-technical stakeholders

• Ability to explain complex AI concepts and trade-offs in a clear, practical, and business-oriented way

• Experience with AI observability, tracing, and monitoring tools

• Experience integrating AI solutions with enterprise platforms and workflows

• Understanding of AI security, data privacy, and governance considerations

• Experience mentoring engineers or technically leading engineering initiatives

• Familiarity with prompt evaluation frameworks, benchmarking, and AI quality validation approaches

• Experience working in Agile product development environments

• Pragmatic…