Forward Deployed Engineer

palindrome.co; United States; Remote; USD 42,000 - 64,000; Full time

Job summary

palindrome.co is seeking a senior Python engineer to build and operate production-grade agentic AI systems for wealth management. You will collaborate with colleagues in London to scope problems and drive Python engineering, model evaluation and deployment into reliable workflows.

Responsibilities include designing, training and evaluating agents, deploying within Azure environments, and turning recurring solutions into reusable components.

Qualifications

• 6+ years building production software with Python.
• Hands-on experience training, evaluating and deploying ML models.
• Cloud infrastructure experience; Azure preferred.
• Knowledge of agentic AI approaches including tools, retrieval, multi-step reasoning, evaluation and guardrails.
• Strong written communication; work effectively with an asynchronous, distributed team.

Responsibilities

• Translate customer needs into clearly defined ML systems, collaborating with 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 requirements change.

Skills

Python

ML deployment

Azure cloud

Agentic AI

Communication

Distributed team

Tools

Azure

PostgreSQL

Microsoft Graph

Job description

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.