{"id":1807097,"url":"https://alion.io/job/cashflo-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":8930,"name":"CashFlo","domain":"cashflo.io","url":"https://alion.io/company/cashflo","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Freshteam","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Anthropic","optional":false},{"name":"ArangoDB","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Neo4j","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Computer Use","optional":true},{"name":"Docker","optional":true},{"name":"ElasticSearch","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GraphRAG","optional":true},{"name":"Java","optional":true},{"name":"Langfuse","optional":true},{"name":"LangSmith","optional":true},{"name":"OCR","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"pgvector","optional":true},{"name":"Spring Boot","optional":true}],"status":"live","first_seen_at":"2026-10-03T19:28:45Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-15T02:01:32Z","board_verified":true,"closed_at":null,"days_open":11,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":11},"description":"Senior AI Engineer - AI Vertical\nTeam: Engineering - AI Vertical\nExperience: 5+ years, including 2+ years building and shipping LLM systems in production\nLocation: Mumbai - Andheri East\nReports to: Head of Engineering\nEmployment Type: Full-time\nAbout CashFlo\nCashFlo is building the next generation of AI-powered Finance & Accounting solutions for businesses.\nIndia sees over $11 trillion in B2B money flows every year, yet businesses typically wait around 70 days to get paid. CashFlo is transforming this ecosystem through technology across Payments, Lending, SaaS and AI.\nOur platform processes ₹20,000+ Cr of invoices every month, serving 300,000+ MSMEs and 1,200+ corporates, with 30+ lenders integrated for credit.\nCashFlo is now building a dedicated AI vertical for the global market, and we're looking for a Senior AI Engineer to join our core engineering team.\nAbout the Role\nWe are building AI agents that can operate core CFO workflows end-to-end - including accounts payable, month-end close, reconciliation, record-to-report, vendor management and compliance workflows.\nThese agents don't just recommend actions. They execute finance processes by interpreting documents, applying accounting and control logic, performing transactions in enterprise systems such as SAP, and escalating genuine exceptions for human review.\nAs a Senior AI Engineer, you will own systems end-to-end, from agent architecture and orchestration to production deployment, evaluation, reliability and scale.\nKey Responsibilities\n1. Build Production AI Agents\nDesign and build autonomous agents for finance workflows such as invoice-to-pay, three-way matching, reconciliation, GL close and exception handling.\nBuild tool and action layers over ERP systems and enterprise applications.\nDesign approval workflows, human-in-the-loop checkpoints and segregation-of-duty controls.\nBuild robust error recovery and ensure complete auditability of agent actions.\nIntegrate with SAP APIs, ERP interfaces, documents and file-based systems.\n2. Agent Memory & Knowledge Systems\nDesign memory and context strategies for long-running agents.\nWork on context windowing, summarization, compaction, retention and forgetting policies.\nBuild finance knowledge graphs covering vendors, invoices, POs, GRNs, GL accounts, contracts, approvals and provenance.\nWork with graph databases such as Neo4j alongside vector search.\n3. Evaluation & Model Strategy\nBuild and improve evaluation frameworks for production AI systems.\nCreate golden datasets, workflow-level metrics and regression gates.\nDevelop automated evaluation and judging systems calibrated against human review.\nMonitor model performance and detect drift on live workloads.\nWork across OpenAI, Anthropic, Google and open-weight models.\nDesign model routing based on quality, latency and cost, including cascading and provider failover.\n4. Scale & Engineering\nOwn the latency, throughput and unit economics of AI workflows at scale.\nMonitor and improve p50/p95/p99 latency and cost-per-workflow.\nBuild and maintain APIs using FastAPI and REST.\nMentor engineers working on AI systems and contribute to engineering best practices.\nRequired Experience\n5+ years of software/ML engineering experience, including 2+ years shipping LLM systems in production.\nProven experience building and deploying multi-step AI agents that perform real actions in production systems.\nStrong understanding of agent failure modes, reliability and control mechanisms.\nExperience designing memory and context strategies for long-running agents.\nHands-on experience building an LLM evaluation framework, including datasets, metrics and automated judging.\nExperience working with at least two LLM model providers or model families.\nExperience migrating or operating live LLM workloads in production.\nExperience operating AI/ML systems at significant scale with measurable production outcomes.\nTechnical Qualifications\nBachelor's/Master's degree in Computer Science, Computer Engineering or a related field.\nAdvanced proficiency in Python.\nStrong experience with modern AI/ML development practices.\nHands-on experience with LangGraph, LangChain, OpenAI Agents SDK, or custom agent orchestration.\nWorking knowledge of graph databases such as Neo4j, Neptune or ArangoDB.\nUnderstanding of graph data modelling, schema design and Cypher/Gremlin.\nStrong API and data engineering fundamentals.\nExperience with FastAPI, PostgreSQL and vector databases.\nExperience deploying cloud-native applications on AWS, GCP or Azure.\nPreferred Experience\nFinance, accounting, audit or ERP/SAP domain exposure.\nExperience with computer-use or browser automation agents.\nKnowledge of GraphRAG and ontology design.\nExperience with document AI/OCR.\nFine-tuning or serving open-weight models.\nLLM observability and tracing using tools such as LangSmith, Langfuse or OpenTelemetry.\nUnderstanding of enterprise AI security, governance and compliance.\nExperience using AI coding agents as part of everyday software development.\nOur Tech Stack\nPython | LangGraph | LangChain | OpenAI | Anthropic | Google AI | FastAPI | PostgreSQL | pgvector | Neo4j | Elasticsearch | Java/Spring Boot | React | GCP | AWS | Docker\nFamiliarity with our exact stack is helpful but not mandatory if you have strong experience with equivalent technologies.\nWhat You'll Work On\nYou will directly contribute to building AI systems that:\nExecute real finance workflows instead of simply generating recommendations.\nInteract with enterprise systems such as SAP.\nProcess large volumes of financial documents and transactions.\nMake finance operations more automated and efficient.\nOperate with strong controls, auditability and human oversight.\nServe enterprise customers at scale.\nWhy Join CashFlo?\nBuild from the ground up: Be part of a new AI vertical targeting the global market.\nHigh-impact work: Your systems will operate on real enterprise finance workflows at scale.\nStrong engineering culture: Work alongside experienced engineers and leadership from top consulting, technology and finance backgrounds.\nOwnership: Own problems end-to-end rather than individual components.\nGrowth: Opportunity to work across AI agents, LLMs, enterprise systems, evaluation and production infrastructure.\n Compensation & Equity: Competitive compensation, incentive structures and meaningful equity in an early-stage company.","description_format":"text","description_chars":6356,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Factoring & Trade 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