Python Architect - AI

Role summary

As Senior Python Architect, you will own the technical strategy and hands-on design for re-platforming the HIVE backend from PL/SQL to Python. You will reverse-engineer the current codebase, document the embedded business logic and data flows, define a target Python architecture (FastAPI, asynchronous processing, clean data-access patterns), establish a pragmatic and low-risk migration strategy with parity validation, and guide the engineering team through delivery. You will be hands-on producing reference implementations and resolving the hardest technical problems while also setting standards, mentoring engineers, and aligning with SFI's enterprise architecture governance (ARB).

Key responsibilities

Current-state assessment & discovery

• Review the existing HIVE system end-to-end PL/SQL packages, procedures, functions, triggers, cursors, scheduled jobs, and the React front-end touchpoints.
• Reverse-engineer and document the embedded business logic, data models, integrations, batch/long-running processes, and dependencies that must be preserved.
• Identify complexity hotspots, technical debt, performance bottlenecks, and risk areas; quantify the conversion effort and produce a phased, prioritized conversion blueprint.

Target architecture & design

• Define the target-state Python architecture: service decomposition, FastAPI API design, asynchronous execution model (async/await, ASGI), data-access layer, configuration, and deployment topology.
• Design patterns for asynchronous and long-running jobs (background workers, task queues, concurrency, idempotency, retries) to replace PL/SQL batch and scheduled processing.
• Establish coding standards, project structure, reusable frameworks/accelerators, and Definition of Done; author Architecture Decision Records (ADRs).
• Define non-functional requirements — performance, scalability, security, observability, and maintainability — and design to meet them.

PL/SQL Python conversion strategy

• Define a low-risk migration approach (e.g., incremental / strangler-fig) with clear sequencing, rollback paths, and coexistence with the current system during transition.
• Establish a rigorous parity and data-reconciliation strategy so converted Python logic produces results equivalent to the original PL/SQL (record counts, field-level validation, transformation-rule verification).
• Decide where logic should move from the database tier into the application tier, and define the data-access strategy against the existing Oracle backend.

Hands-on engineering & leadership

• Build reference implementations / proofs-of-concept for the highest-risk conversion patterns; set the template the team follows.
• Provide technical leadership, code review, and mentoring to Python and data engineers within the HIVE Fusion Team.
• Drive engineering quality: automated testing (pytest), CI/CD, code quality gates, and regression coverage for converted modules.

Collaboration & governance

• Partner with SFI HIVE / Digital Labs stakeholders to validate business logic and acceptance criteria.
• Align designs with SFI's Architecture Review Board (ARB) and enterprise standards for security, integration, and platforms.
• Where applicable, leverage Ascendion's AAVA platform and AI-assisted tooling to accelerate code understanding, conversion, and test generation.

Required skills & experience (must-have)

• Python expert (3.10+): idiomatic, production-grade Python with strong design and OOP/functional fundamentals.
• FastAPI: deep, hands-on experience designing and building REST APIs with FastAPI (Pydantic, dependency injection, ASGI servers such as Uvicorn/Gunicorn).
• Asynchronous programming: strong command of asyncio, async/await, concurrency, and async I/O; designing asynchronous and long-running job execution.
• PL/SQL & SQL (deep): expert ability to read, reverse-engineer, and translate large PL/SQL codebases — packages, procedures, functions, triggers, cursors — and tune SQL for performance.
• Oracle database: solid working knowledge of Oracle (the current HIVE backend), data modeling, and query optimization.
• AWS: hands-on experience designing, deploying, and running Python services on AWS — e.g., Lambda, ECS/EKS, API Gateway, RDS, S3, and IAM — including cost-aware, secure, and scalable cloud-native patterns.
• Full-stack awareness: comfortable across the stack, including integration with a React front end and clean API contracts.
• Application modernization / migration: proven track record converting or re-platforming legacy systems to modern Python services, with parity validation and zero-regression discipline.
• Architecture: demonstrated experience as a solution/application architect — target-state design, NFRs, ADRs, and setting engineering standards.
• Engineering practices: Git/GitHub, CI/CD, automated testing (pytest), containerization (Docker/Kubernetes).
• Experience: typically 10+ years in software engineering with 4+ years in a senior architect capacity on data-intensive, business-critical systems.

Preferred / nice-to-have

• Data access / ORM frameworks (e.g., SQLAlchemy), task queues / background workers (e.g., Celery, arq, RQ), and message/event-driven patterns.
• Cloud & data platforms: Azure, GCP (incl. Gemini Enterprise); Databricks; Power BI / semantic layers.
• AI / agentic engineering, GenAI-assisted code conversion, and exposure to AI acceleration platforms (e.g., AAVA).
• Warehouse-management / supply-chain or food & CPG / manufacturing domain exposure.
• Observability (logging, metrics, tracing) and API security best practices (authN/authZ, secrets management).