{"id":1119629,"url":"https://alion.io/job/hedgineer-front-office-engineer","title":"Front Office Engineer","company":{"id":3812191,"name":"Hedgineer","domain":"hedgineer.ai","url":"https://alion.io/company/hedgineer-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"ClickHouse","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"DuckDB","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Pandas","optional":false},{"name":"Polars","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"Claude Code","optional":true},{"name":"dbt","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-09-22T18:16:08Z","employer_posted_date":null,"last_verified_at":"2026-09-22T18:16:08Z","board_verified":false,"closed_at":null,"days_open":47,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":47},"description":"This is a front-office engineering role performed on behalf of clients. You will build and operate systems used daily by portfolio managers, traders, research analysts, and operations teams at sophisticated hedge funds, working directly with those teams to refine and deliver solutions. The work is often ambiguous rather than fully specified, and you will be expected to turn questions or issues into production systems by ingesting data, modeling it correctly, computing analytics, exposing it through APIs, and standing behind the results. Correctness and speed both matter, as the output supports trading, risk, and reporting decisions. You will build on shared core infrastructure such as APIs, data pipelines, and analytics engines, focusing on backend and analytical systems rather than UI ownership.\nResponsibilities:\nTurn ambiguous requests from client investment and operations staff into specifications and production systems.\nDesign and maintain high-performance APIs using Python and frameworks such as FastAPI.\nBuild and operate reliable ingestion and transformation pipelines for market, position, and reference data using orchestration tools such as Airflow, Dagster, or Prefect.\nArchitect analytical and transactional data models that support evolving business needs.\nImplement analytics layers for performance, exposure, and risk calculations using linear algebra and time-series operations with tools such as Pandas or Polars.\nBuild reconciliation, validation, and monitoring processes to ensure data quality.\nMaintain metric definitions and a semantic layer so metrics remain consistent across dashboards, reports, and AI agents.\nTrace discrepancies through pipelines back to source data and debug numerical issues, not just application errors.\nWork directly with client investment, research, and operations teams, alongside engineers across distributed teams, to gather requirements, iterate, and support live workflows.\nRequirements:\n3-10 years of engineering experience, with at least 2 years in or adjacent to financial markets.\nWorking knowledge of investment data models, including positions, securities, transactions, P& L, exposure, and returns, and how front-office teams use them.\nDirect experience at a hedge fund, asset manager, proprietary trading desk, sell-side desk, fund administrator, or a vendor serving these clients.\nDegree in computer science, engineering, mathematics, or a related quantitative field, or equivalent practical experience.\nStrong Python and SQL skills.\nHands-on experience building APIs using FastAPI, Flask, or Django, with a solid understanding of RESTful and secure API design.\nProduction experience with data pipelines and orchestration tools such as Airflow, Dagster, or Prefect.\nExperience with analytical databases and data warehouses such as Snowflake, ClickHouse, DuckDB, SQL Server, or Databricks, along with deliberate data modeling.\nExperience with analytical libraries such as Polars and Pandas for computationally heavy workloads.\nFamiliarity with data quality frameworks and monitoring.\nHands-on experience with Docker and containerized development.\nExposure to cloud platforms such as Azure, AWS, or GCP and cloud-native architectures.\nComfort with ambiguity and the judgment to ask the right questions of non-technical stakeholders.\nExcellent communication skills for translating technical concepts to investment and operations staff.\nNice To Have:\nExperience with portfolio analytics, risk platforms, or fund accounting systems.\nComfort with complex models such as factor risk, attribution, or reconciliation.\nFamiliarity with AI development workflows and agentic frameworks such as Claude Code, LangGraph, MCP servers, or RAG.\nFamiliarity with event-driven and streaming architectures for real-time and batch data processing.\nHands-on exposure to dbt and local analytics with DuckDB.\nExperience optimizing performance on large time-series workloads.\nTrack record of shipping in fast-paced, client-facing environments.\nAbility to read frontend code and collaborate effectively with UI teams.","description_format":"text","description_chars":4067,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Software & Embedded Finance","Financial 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