Build and deploy AI-powered tools, agents, MCP integrations, and workflow automations. Own packaging, testing, hosting, monitoring, and production release cycles. Develop evaluation sets, regression checks, and human review processes to validate AI outputs. Use Claude and other LLM platforms, Python, SQL, React, and Docker. Collaborate across teams to identify automation opportunities, document technical solutions, assess data confidentiality, and communicate results to technical and non-technical stakeholders.
About Tristone Strategic Partners LLP- Tristone Strategic Partners is a financial services firm based in
Mumbai that provides investments and accounting-related support services and advisory services to
international clients such as various investment funds, hedge funds, wealth management firms,
start-ups & corporates located across different geographies.
About the role-
Tristone is embedding agentic AI directly into its workflows and systems. As a member of the Agentic
AI engineering team, you'll help build agents, MCP servers, and evaluation loops that make AI
generated code reliable, auditable, and fast to ship. You'll work closely with senior members of
Tristone to deliver pragmatic, high-impact AI integrations at scale.
Key Responsibilities-
- Designing, building, and deploying AI-powered tools, agents, and workflow automations for
use across the firm.
- Working hands-on with the Claude ecosystem - Cowork, Claude Code, Connectors, Skills, and
Plugins - alongside other AI platforms (ChatGPT, Gemini, and others).
- Owning the end-to-end deployment lifecycle for AI tools and agents, including packaging,
testing, hosting, and monitoring in production.
- Collaborating with teams across the firm to identify opportunities to automate repetitive or
manual processes using AI and workflow orchestration tools.
- Reviewing and validating AI-generated outputs to ensure accuracy, completeness, and
reliability before they reach internal or client-facing use.
- Staying current on evolving AI capabilities and evaluating new tools and platforms for potential
adoption.
- Documenting technical approaches clearly and communicating outcomes to both technical
and non-technical stakeholders.
- Exercising sound judgement across AI workflows: assessing which client and fund data may be
sent to which model, working exclusively through approved endpoints and enterprise tooling,
and upholding the confidentiality obligations expected in a financial services environment.
- Complying with IT policies and procedures.
- Maintaining the security of information at all times.
Requirements
- AI Tools & LLMs - Hands-on experience using platforms such as Claude, ChatGPT, Gemini, or
Copilot, with the prompt-engineering skill to get consistent, high-quality outputs across
models.
- Agents and MCP - Hands-on experience building agentic workflows and integrating external
tools through MCP servers or equivalent tool-use frameworks. Alongside this, a systematic
approach to validating model output: maintained eval sets, regression checks before release,
and structured human review loops, rather than ad-hoc spot checking.
- Demonstrated Projects - Self-built AI projects or agents you can showcase, covering both
standard and custom workflow-specific use cases. Projects built with Claude (Cowork, Claude
Code, Connectors, Skills, Plugins) are particularly valued.
- Prompt Engineering - Ability to structure prompts effectively - framing tasks clearly, refining
outputs, and adapting instructions to get consistent, high-quality results across different AI
models.
- Build & Deploy - Experience taking an AI tool or agent from build to production; packaging
(Docker), hosting, and monitoring in a real environment.
- Technical Skills - Python for scripting, API calls, and data pre-processing; SQL for querying
structured data; React for simple internal dashboards; AI coding tools such as Claude Code or
ChatGPT Codex.
- Communication & Collaboration - Good communication skills, with the ability to work
effectively across teams and explain technical work clearly to non-technical stakeholders
Qualification-
- Bachelor’s or Master’s degree in computer engineering, Computer Science, or any other
relevant specialization (e.g., AI/ML, Data Science, IT).
Experience-
- 1+ years of relevant experience in AI/ML engineering, software development, or applied AI
projects.
- You should be able to clearly demonstrate how you have used AI tools - including Claude - to
build, deploy, and improve efficiency, quality, or speed in a professional context.
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