Sr. Software Engineer

About the role

We're hiring a Senior Software Engineer who thrives at the intersection of large-scale systems, intelligent automation, and meaningful business impact. You'll help design and deliver backend foundations that power agentic systems operating over massive volumes of enterprise data—text, tables, and beyond. You'll pair sharp architectural judgment with hands-on engineering, collaborating with AI/ML, Product, QA, and SRE to turn complex workflows into simple, reliable, and delightful experiences.

This role suits an engineer with a strong systems mindset, craftsmanship standards, and a growth-oriented, collaborative spirit.

What you'll do

• Design, implement, and operate backend components and APIs for agentic systems that process/reason over structured and unstructured data.
• Build resilient, observable, maintainable Python services (FastAPI preferred) with strong typing, CI/CD, and clear interfaces (REST/gRPC).
• Partner with AI/ML to integrate intelligent workflows safely and efficiently in production (guardrails, performance, reliability).
• Architect for performance, scalability, and reliability: async I/O, caching, data modeling/tuning (PostgreSQL or similar), distributed coordination, and backpressure strategies.
• Collaborate with Product, Data, QA, and SRE to make pragmatic, high-impact decisions; decompose projects into milestones tied to measurable outcomes.
• Co-own operational excellence: containerization, feature flags, progressive rollouts (canary/blue-green), observability, and post-release validation.
• Contribute to engineering culture—mentor peers, evolve patterns, raise the bar on code quality, testing strategy, and documentation.

Key Technical Expertise

• Deep expertise in Python backend development (FastAPI preferred) and modern async programming patterns.
• API & integration design with REST/gRPC, secure auth (OAuth2, JWT), and clear domain boundaries.
• Solid grasp of distributed systems, event-driven architectures, and microservices (idempotency, retries, timeouts).
• Strong data performance skills: schema design, query optimization, caching, and throughput/latency trade-offs.
• Practical observability: structured logging, metrics, tracing, health checks/PRV.
• Hands-on with Docker, Kubernetes, and cloud-native deployment (AWS/GCP).
• Familiarity with analytics fundamentals (A/B testing, basic statistics) and data pipelines.

Qualifications

• 5+ years building production backends in Python (typing, async I/O, CI/CD).
• Proven ability to translate technical concepts into business value and communicate effectively with both technical and non-technical partners.
• Strong analytical problem-solving; able to turn ambiguity into concrete, elegant solutions.
• Track record architecting performant, scalable systems that evolve under growing load and complexity.
• Experience partnering cross-functionally with Product, SRE, and AI/ML.
• Resourceful, self-starting, and committed to continuous improvement—for the system and yourself.
• Passion for impactful technology and delivering high-quality software.

Nice to Have

• Experience with LangGraph and agentic workflows (state graphs, tools, memory, routing).
• Exposure to DDD, CQRS, EDA, or streaming platforms (Kafka/Pub/Sub).
• Knowledge of Go/Rust/C++ or other systems-level languages.
• Background with enterprise data platforms, integrations, or real-time systems.

Soft Skills & Mindset

• Communicates with clarity and empathy; values partnership as much as code.
• Thrives in ambiguity; owns problems end-to-end and delivers outcomes.
• Mentors others, shares patterns, and fosters an inclusive, learning-oriented team.
• Curious and adaptable; balances principled engineering with pragmatic delivery.
• Connects technical decisions to user impact and business results.
• Embodies a growth mindset—learn, experiment, refine.

Success Indicators

You'll measure success not just by what you ship, but by how you elevate the system and the team:

• Reliable delivery: milestones achieved predictably and with quality.
• System excellence: services run efficiently, scale gracefully, and meet latency/availability goals.
• Collaboration: strong cross-team relationships, clear communication, healthy design debate.
• Impact: measurable improvements to reliability, scalability, and developer velocity.
• Growth: visible mentorship, pattern adoption, and shared learning across the team.