Python Developer

Start Date: 1st September 2026

Duration: 3 months contract (Good chance of extension)

Location: Remote

Project: Implementation

Job Summary: We are seeking a Senior Python Engineer with strong DevOps expertise who brings both technical mastery and a proactive mindset to our engineering team. In this role, you won't just write application code or take tickets; you will act as a technical motor, taking full ownership of our backend applications and the automated CI/CD pipelines that deliver them. Our primary challenges revolve around ultra-low-latency, high-throughput backend applications and rock-solid automation. You will lead the charge in optimizing Python code execution within AWS Lambda environments, designing low-latency DynamoDB data structures, and building robust, fully automated Terraform and Jenkins infrastructure pipelines.

Key Responsibilities & Deliverables: Build for Speed: Design, optimize, and maintain hyper-fast microservices and event-driven architectures on AWS Lambda, focusing on low memory footprints, minimal cold-start times, and ultra-fast execution. Master Infrastructure as Code (IaC): Lead the provisioning, modularization, and maintenance of cloud infrastructure using Terraform, ensuring environment parity across development, staging, and production. Build & Manage CI/CD Pipelines: Design, optimize, and maintain automated deployment pipelines using Jenkins, implementing automated testing, security scanning, blue/green or canary deployments, and zero-downtime releases. Optimize the Data Layer: Think scalable, low-latency data access patterns in Amazon DynamoDB using Single-Table Design, GSIs/LSIs, and stream-based processing. Be proactive: Proactively evaluate current code bottlenecks and pipeline friction points, challenge established paradigms with data-driven arguments, and propose innovative architectural improvements.

Mindset & Ownership (Must-Haves): Self-Directed & Autonomous: You thrive in environments where you determine the _'how'_ after being given the business goals. You don't wait for permission to fix broken things or improve inefficient deployment workflows. Driven / Technical Motor: You bring high energy and initiative, actively inspiring team members and driving project velocity forward across both development and operational tasks. Solution-Oriented: When faced with system or deployment bottlenecks, you don't just present problems; you come with 2–3 viable solutions along with their trade-offs. Technical Qualifications 8+ Years of Senior Software & DevOps Engineering Experience with Python as your primary backend language. Expert Terraform Knowledge: Deep experience managing multi-region AWS environments using reusable Terraform modules, remote state management, and infrastructure automation best practices. Advanced Jenkins Pipeline Engineering: Hands-on experience writing complex Jenkinsfiles (Declarative & Scripted), pipeline shared libraries, and automating build/test/deploy cycles for serverless architectures. Deep AWS Serverless Expertise: Production mastery of AWS Lambda, API Gateway, SQS/SNS, and EventBridge in high-volume environments. Python Performance Optimization: Proven experience optimizing Python application code for raw speed (e.g., leveraging {{{}asyncio{}}}, profiling execution bottlenecks, reducing memory allocations, and mitigating Lambda cold starts).Expert DynamoDB Knowledge: Advanced experience with non-relational database design (Single-Table Design patterns, GSI/LSI optimization, TTL, DynamoDB Streams, and capacity management).Observability & Operational Rigor: Experience with CloudWatch, AWS X-Ray, Datadog, or Open Telemetry to profile, debug, and monitor distributed systems and deployments.

Nice-to-Haves: Experience running Jenkins controllers on AWS (e.g., dynamic build agents on AWS ECS/Fargate or Kubernetes).Knowledge of alternative runtime acceleration (e.g., AWS Lambda Provisioned Concurrency, custom runtimes, PyPy, or Cython).Experience with serverless integration testing frameworks (e.g., PyTest-AWS, LocalStack) within Jenkins pipelines. Familiarity with streaming data engines like AWS Kinesis or Apache Kafka.