FSM is building the next generation of AI-powered financial systems — where accounting, operations, and data applications work together intelligently. As a Senior Data Engineer, you'll be both a core builder of that platform and a primary technical point of contact for clients as they navigate that transformation.
Most of your week is deep technical work — cloud infrastructure, data pipelines, and AI agents. A meaningful part of it is direct conversation with client accounting, finance, and operations teams, leading discovery and translating what you learn into what we ship. You're equally comfortable debugging an IAM policy, pairing with an AI Agent Engineer, and running a discovery session with a client's Controller.
You'll work closely with the Head of Engineering and CTO , alongside FSM's junior and senior engineers and offshore team , and serve as a trusted technical voice clients rely on throughout the engagement.

Cloud & Platform Engineering — the foundation
Design, build, and operate FSM's AWS infrastructure: Maintain and extend our templating/scaffolding system (copier-based) so new client pipelines and agents deploy fast and stay consistent.
Data Engineering & Integration
Build and maintain data pipelines and the S3-based data platform feeding our agents and BI (DBT, AWS QuickSight).
Architect and build integrations across accounting, ERP, CRM, and operational apps — QuickBooks, HubSpot, Stripe, Plaid, Box, Slack — into a clean, source-agnostic layer.
Ensure consistent, accurate, reconciled data flow.
Agent Development & Implementation
Design and code intelligent agents that act on financial data through APIs and natural-language interfaces, plugging into FSM's orchestration layer.
Develop the logic frameworks, contracts, and prompts that govern how agents interpret data, take action,



and communicate results — including human-in-the-loop controls.
Test and refine agent performance with real client data — ensuring security, auditability, and alignment with accounting principles.
Walk clients through agent behavior and outputs directly, building their confidence and trust in the automation.
Lead discovery sessions with client accounting, finance, and operations teams to understand their workflows, data challenges, and automation needs.
Serve as the primary technical liaison between FSM and the client — explaining findings, options, and trade-offs in terms non-technical stakeholders can act on.
Identify opportunities where AI agents can replace repetitive processes, improve reconciliation, or enhance insight delivery.
Create comprehensive documentation of automations, agent behaviors, infrastructure, and client-specific implementations.
Share progress, blockers, and technical decisions clearly — and early — across Engineering, Client Delivery, and CSM, not just with the AI Agent Engineering team.

5+ years building and operating production systems on AWS , with real depth in serverless (Lambda/API Gateway), infrastructure-as-code (CloudFormation or similar) , and cloud security (IAM, secrets, multi-tenancy).

- Robust data engineering : Python, SQL, data pipelines, and a modern data stack (DBT, S3/data-lake patterns, a BI tool).
- Experience integrating accounting/ERP/CRM platforms (QuickBooks, HubSpot, or similar) via APIs, webhooks, or connectors.




- Comfort with LLM-based tools and APIs — prompt design and evaluating agent outputs for accuracy and reliability.
- Hands-on experience using AI coding tools (e.g., Claude Code) as part of your daily development workflow — planning, building, reviewing, and documenting code with them.
- Demonstrated experience working directly with clients or business stakeholders — leading discovery, presenting findings, managing expectations, not just coding behind the scenes.
- You communicate clearly under pressure — status, trade-offs, and blockers surfaced early — with technical and non-technical audiences alike.
- Excellent verbal and written English; Bonus Points:

Experience building LLM/AI agents or orchestration systems.
Working knowledge of accounting (reconciliations, journal entries, chart of accounts, financial reporting) — or a genuine willingness to learn the domain; Experience taking a team from bespoke work toward standardized, documented process.
AWS (Lambda, API Gateway, SQS, RDS + RDS Proxy, Cognito, Secrets Manager, CloudFormation, CloudWatch) · Python · GitHub Actions · Claude Code · copier · DBT · S3 · AWS QuickSight · LLM agents (Claude) · QuickBooks, HubSpot, Stripe, Plaid, Box, Slack

Discovery sessions consistently surface automation opportunities that convert into shipped agents and integrations.
The platform you build is secure, multi-tenant, and reliable - deployments are repeatable and don't bottleneck on any one person.
Agent deployments are accurate, auditable, and aligned with sound accounting principles — earning continued client confidence.
Security and compliance stay audit-ready - SOC 2 / Vanta controls and checks are maintained without last-minute fire drills.
Compensation commensurate with experience
Ongoing education and training
Bonuses

📌 Senior Data Engineer - AI & Data (India)
🏢 FinStrat Management
📍 India