Location:
Mumbai, India Work Location Preference: Candidates based in Mumbai or nearby locations preferred Employment Type: Full-Time We are looking for engineers who have built and owned complex production systems
- not simply contributed to them. Industry: Financial Technology (FinTech), Fund Accounting, Financial Services, AI-Driven Enterprise Applications

About The Role
We are seeking a highly skilled, hands-on Senior Backend Engineer with demonstrated experience designing, developing, and owning complex enterprise-grade backend applications. The ideal candidate is a proven builder who has independently taken a substantial software service or application module from initial requirements through architecture, development, testing, deployment, and production support. You will contribute to an AI-assisted financial operations platform designed for fund controllers, supporting trial balances, reconciliation workflows, financial calculations, multi-level approvals, and accounting processes. This position requires strong backend engineering fundamentals, database architecture expertise, production AI agent development experience, and a commitment to financial data accuracy, consistency, and auditability.

Key Responsibilities
Backend Engineering & Architecture
• Design, develop, and maintain scalable, enterprise-grade backend applications.
• Own backend services throughout the complete software development lifecycle.
• Translate complex business requirements into technical specifications and architecture.
• Design robust REST APIs, application services, database schemas, and business logic.
• Implement authentication, authorization, role-based access control, and secure data access.
• Build APIs supporting both traditional web applications and AI-driven agents.
• Ensure reliability, performance, data integrity, and production readiness.
• Troubleshoot complex production issues and provide long-term technical solutions. Financial Application Development
• Develop backend services supporting fund accounting and financial operations.
• Implement workflows involving trial balances, general ledgers, journal entries, and accounting period close.
• Support financial reconciliations, approvals, audit trails, and maker-checker controls.
• Design systems capable of handling currency precision, rounding, financial dates, and accounting periods.
• Ensure financial calculations are deterministic, reproducible, and auditable.
• Collaborate directly with finance, accounting, and business stakeholders. AI Agent Development
• Design, develop, and deploy production-grade AI agents integrated with enterprise applications.
• Build LLM-powered workflows involving multiple steps, tools, and contextual information.
• Implement structured outputs with schema validation.
• Develop evaluation frameworks to measure AI agent accuracy, reliability, and performance.
• Integrate human-in-the-loop approval mechanisms for sensitive financial actions.
• Ensure AI agents retrieve information, identify exceptions, and support decision-making while deterministic backend services perform financial calculations.
• Persist agent workflow state, execution results, and relevant audit information in databases. Database, Infrastructure & Quality Engineering




• Design and implement scalable database architectures and optimized schemas.
• Work with PostgreSQL, Snowflake, and other enterprise data platforms.
• Implement infrastructure-as-code for consistent application deployments.
• Develop comprehensive unit and integration tests.
• Mock external services and network calls during automated testing.
• Maintain production quality through code reviews, performance optimization, and systematic debugging. Required Technical Skills Technology / Capability Requirements Backend Programming Python and Java; comparable enterprise backend technologies considered Python Frameworks FastAPI, Pydantic, SQLAlchemy Java Frameworks Spring Boot, Maven Databases PostgreSQL, Snowflake, database schema design API Development REST APIs, API contracts, versioning, idempotency, error handling Application Architecture Enterprise web services, domain modeling, service boundaries Security Authentication, authorization, role-based permissions Financial Data Handling Currency precision, decimal calculations, rounding, periods, time zones Development Methodology Specification-driven software development Cloud & Infrastructure Infrastructure as Code; Azure experience preferred Testing Unit testing, integration testing, mocking AI Engineering LLM agents, tool calling, workflow orchestration, structured outputs Agent Quality Evaluation frameworks, human approvals, persistent workflow state Mandatory Qualifications
• Minimum 5 years of professional backend software engineering experience.
• Proven experience independently architecting, building, and owning a complex production backend service or significant application module.
• Strong understanding of enterprise application architecture, API design, database modeling, and transactional integrity.
• Production backend development experience using Python, Java, or comparable technologies.
• Hands-on experience designing and implementing database architectures.
• Experience using written specifications to drive requirements, implementation, and verification.
• Demonstrated ability to deliver production-quality, thoroughly tested applications.
• Hands-on ownership of at least one production AI agent workflow, including LLM integration, tool calls, structured outputs, evaluations, and human-in-the-loop controls.
• Strong analytical, troubleshooting, and technical decision-making skills.
• Ability to work independently with business stakeholders and translate ambiguous requirements into working solutions. Significant: Specific programming languages and frameworks are flexible for exceptional backend engineers who demonstrate genuine end-to-end ownership. Production AI agent development and substantial backend service ownership remain essential. Preferred Domain Experience Candidates with experience in one or more of the following areas will receive priority consideration:
• Private Equity, Private Credit, Hedge Funds,



and Alternative Asset Management
• Fund Accounting, Fund Administration, and Portfolio Accounting
• Corporate Accounting, ERP, General Ledger, and Financial Close Management
• Banking, Capital Markets, BFSI, and Financial Technology Preferred Financial Knowledge
• General Ledger (GL), Journal Entries, and Trial Balance
• Net Asset Value (NAV), Valuations, and Financial Marks
• Accruals, Fee Calculations, and Period-End Close
• Financial Reconciliation and Exception Management
• Audit Trails, Financial Controls, and Maker-Checker Approval Workflows Additional Preferred Skills
• Microsoft Azure cloud platform.
• Production implementation of Model Context Protocol (MCP) servers.
• Agentic AI solutions developed for accounting or financial workflows.
• Experience with high-volume, data-intensive financial applications.
• Experience designing systems with strict requirements for financial data correctness and auditability. What Makes an Ideal Candidate? We Are Particularly Interested In Engineers Who Can Demonstrate End-to-end ownership: Independently built and maintained a substantial production service. Architectural judgment: Can explain design decisions, alternatives, and technical tradeoffs. Production accountability: Has handled real-world incidents, data issues, and performance challenges. Business understanding: Can collaborate directly with finance and accounting stakeholders. Engineering discipline: Prioritizes correctness, reliability, automated testing, and maintainability. Practical AI expertise: Has built real production AI workflows rather than only experimenting with LLM APIs. Ownership mindset: Can turn an ambiguous business problem into a deployed and supported technical solution. Candidate Screening Questions Candidates Should Be Prepared To Discuss
• Describe a complex backend service you personally designed and built from scratch. What were the major architectural decisions?
• Have you implemented backend services in Python, Java, or comparable technologies? Which frameworks and databases did you use?
• Have you worked on financial applications involving general ledgers, trial balances, reconciliations, or financial transactions?
• How have you handled currency precision, rounding, transaction consistency, and financial data integrity?
• Describe a production AI agent you personally built. What tools, workflows, structured outputs, evaluation mechanisms, and human approvals did it include?
• Have you designed Snowflake or PostgreSQL database architectures for large-scale applications?
• What is your experience with Infrastructure as Code and cloud deployments, particularly Azure?
• Can you describe a serious production issue you resolved in a system you owned? Candidate Submission Requirements Interested Candidates Should Share The Following Updated resume Current location Total years of experience Relevant backend development experience Experience with Python, Java, PostgreSQL, and Snowflake Financial services or accounting domain experience Production AI agent development experience Current compensation (CTC) Expected compensation (CTC) Notice period / earliest joining availability We are looking for engineers who have built and owned complex production systems
- not simply contributed to them.

📌 Senior Backend Engineer (Mumbai)
🏢 First Soft Solutions
📍 Mumbai