Forward Deployed Engineer

Role overview Build and operate production agentic AI systems for wealth management customers. Working with colleagues in London, you’ll help scope customer problems and take responsibility for the Python engineering, model evaluation and deployment needed to turn those problems into reliable workflows.

Responsibilities - Translate customer needs into clearly defined machine learning systems, collaborating in scoping discussions with technical and business stakeholders. - Design, train and evaluate agents for workflows such as document review, fact finding, compliance monitoring and suitability writing. - Deploy systems within customer Azure environments, including identity, secrets and private network configuration. - Define evaluation measures and test sets, compare model behavior with customer ground truth, and iterate on results. - Turn recurring field solutions into reusable Python components for the wider platform. - Make technical decisions across the system lifecycle and improve production quality when behavior or requirements change.

Requirements - At least six years building production software, with strong day-to-day Python skills. - Hands-on experience training, evaluating and deploying machine learning models in production. - Practical cloud infrastructure experience; Azure is preferred, while AWS or GCP experience is relevant. - Sound understanding of agentic AI approaches, including tool use, retrieval, multi-step reasoning, evaluation and guardrails. - Strong written communication and ability to work effectively with an asynchronous, distributed team.

Nice to have - Customer-facing engineering experience. - Background in wealth management, fintech or another regulated field. - Familiarity with Python backend frameworks, Azure AI services, PostgreSQL, model evaluation tools, Microsoft Graph or CRM integrations.

Benefits and work setup - Based in Pune or remote within India, with regular working-hour overlap with a London team. - Competitive salary and equity are offered; the role also includes ownership of technical decisions and exposure to senior customer leaders.