Senior Backend Engineer - Financial Applications & AI Agents

Location: Mumbai, IndiaWork Location Preference: Candidates based in Mumbai or nearby locations preferred

Employment Type: Full-TimeWe 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 ApplicationsAbout The RoleWe 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 ResponsibilitiesBackend Engineering & ArchitectureDesign, 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 DevelopmentDevelop 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 DevelopmentDesign, 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 EngineeringDesign 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 SkillsTechnology / CapabilityRequirementsBackend ProgrammingPython and Java; comparable enterprise backend technologies consideredPython FrameworksFastAPI, Pydantic, SQLAlchemyJava FrameworksSpring Boot, MavenDatabasesPostgreSQL, Snowflake, database schema designAPI DevelopmentREST APIs, API contracts, versioning, idempotency, error handlingApplication ArchitectureEnterprise web services, domain modeling, service boundariesSecurityAuthentication, authorization, role-based permissionsFinancial Data HandlingCurrency precision, decimal calculations, rounding, periods, time zonesDevelopment MethodologySpecification-driven software developmentCloud & InfrastructureInfrastructure as Code; Azure experience preferredTestingUnit testing, integration testing, mockingAI EngineeringLLM agents, tool calling, workflow orchestration, structured outputsAgent QualityEvaluation frameworks, human approvals, persistent workflow stateMandatory QualificationsMinimum 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.Important: 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 ExperienceCandidates with experience in one or more of the following areas will receive priority consideration:Private Equity, Private Credit, Hedge Funds, and Alternative Asset ManagementFund Accounting, Fund Administration, and Portfolio AccountingCorporate Accounting, ERP, General Ledger, and Financial Close ManagementBanking, Capital Markets, BFSI, and Financial TechnologyPreferred Financial KnowledgeGeneral Ledger (GL), Journal Entries, and Trial BalanceNet Asset Value (NAV), Valuations, and Financial MarksAccruals, Fee Calculations, and Period-End CloseFinancial Reconciliation and Exception ManagementAudit Trails, Financial Controls, and Maker-Checker Approval WorkflowsAdditional Preferred SkillsMicrosoft 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 DemonstrateEnd-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 QuestionsCandidates Should Be Prepared To DiscussDescribe 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 RequirementsInterested Candidates Should Share The FollowingUpdated resumeCurrent locationTotal years of experienceRelevant backend development experienceExperience with Python, Java, PostgreSQL, and SnowflakeFinancial services or accounting domain experienceProduction AI agent development experienceCurrent compensation (CTC)Expected compensation (CTC)Notice period / earliest joining availabilityWe are looking for engineers who have built and owned complex production systems - not simply contributed to them.