Senior Backend Engineer (Python+AWS+Fintech)

About the Role

We are hiring a Senior Backend Engineer (Python / AWS) to build a production automated order placement system for an AI-driven systematic trading client.

The system turns trading signals into broker orders, tracks every order through its lifecycle and feeds fill results back to the client's portfolio optimizer. It must run reliably and safely, with a full audit trail.

Responsibilities
1. Order management and trading logic

• Design and build the order management layer: an explicit order state machine (new, sent, partially filled, filled, cancelled, rejected, expired).
• Make order submission idempotent, so retries and reconnects never create duplicate orders.
• Build a pluggable broker adapter for submit, cancel, replace, status and fill events over REST, WebSocket or FIX APIs.
• Implement pre-trade risk checks: position and notional limits, per-order size limits, restricted lists, price sanity checks and a manual plus automatic kill switch.
• Aggregate fills into positions and residual quantities, and pass a clean state snapshot to the optimizer each cycle.
• Implement configurable policies for unfilled orders: cancel, re-price or carry over. 2. Reliability, reconciliation and audit
• Build intraday and end-of-day reconciliation of orders, fills and positions against broker records, with break reports and alerts.
• Maintain an immutable, event-sourced audit trail of every signal, order, broker message and fill.
• Handle broker rate limits, outages and undocumented behaviour with retries, backoff and stale-order detection.
• Test partial fills, rejects and disconnects end to end in paper trading before any live order is placed. 3. Backend engineering on AWS
• Build asynchronous Python services integrated with the client's existing codebase.
• Use Redis for fast order and position state, caching, locks and messaging.
• Deploy on AWS (ECS, Lambda or EKS) with the platform engineer, using Terraform, CI/CD and separate dev, paper and prod environments.
• Add metrics, tracing and structured logs, with dashboards and alerts for latency, errors and stuck orders. 4. Ownership and collaboration
• Take part in discovery and the architecture proposal, and raise concerns about design or requirements early.
• Write runbooks and architecture docs.
• Review code and share best practices with the team.

Requirements

• 5–7+ years of experience in backend development, with production systems you have owned end to end.
• B.E. / B.Tech / B.S. in Computer Science or a related field. Candidates without these degrees but with strong experience in the areas below will be considered.
• Strong Python skills, including asyncio, typing, testing and a modern framework such as FastAPI.
• Hands-on production experience with Redis: data structures, pub/sub or streams, distributed locks and persistence trade-offs.
• Strong AWS experience (ECS/EKS, Lambda, SQS/SNS, RDS, IAM, Secrets Manager, CloudWatch) and Infrastructure as Code (Terraform, CloudFormation or equivalent).
• Solid work with PostgreSQL or another relational database, including transactions, consistency and schema design for financial records.
• Proven design of distributed, event-driven systems: idempotency, exactly-once or at-least-once processing, retries, failure handling and state machines.
• Finance knowledge is a must: positions, P&L, notional exposure, portfolio rebalancing, and how trades are booked and settled.
• Trading knowledge is a must: order lifecycle, order types (market, limit, stop), partial fills, slippage, pre-trade risk controls and broker reconciliation.
• Hands-on experience integrating with at least one broker or exchange API.
• Experience with Docker, CI/CD pipelines and observability tools (Prometheus/Grafana, Datadog or CloudWatch).
• An ownership mindset: you drive work to production, raise risks early and write clear documentation.
• Experience mentoring engineers and running code reviews.
• Clear written and spoken English, for working directly with the client's engineering leadership.

Nice to have

• Prior work at a hedge fund, prop trading firm, brokerage, fintech or quant platform.
• Built an order management system (OMS) or execution management system (EMS) that went live.
• Exposure to systematic or quantitative trading: signals, portfolio optimizers, backtesting and paper trading.
• Execution-quality work: order slicing (TWAP/VWAP), slippage and transaction-cost analytics.
• Apache Kafka or Kinesis for event streaming.
• Awareness of audit, compliance and data-retention needs in regulated trading.