Staff Software Engineer - AI

Overview

Staff Software Engineer - AI at Element34, TechGrove by Banyan Software. A hands-on Staff Engineer role with no direct reports, building an AI-native platform for the end-to-end test lifecycle.

What you'll do

• Build the AI core of the platform: design and ship LLM-powered features and autonomous agents that author tests, diagnose failures, find root causes and repair broken tests.
• Build RAG and retrieval systems over test artifacts, logs, traces, DOM snapshots and code, owning chunking, embeddings, hybrid search, ranking and context construction, and measure retrieval quality rigorously.
• Make AI production-grade: build evaluation harnesses, guardrails, observability, cost and latency controls, and fallbacks so agents behave predictably in enterprise environments, including self-hosted and air-gapped ones.
• Design and build core platform systems in Java or Go, including session orchestration, scheduling, resource management and high-concurrency services behind thousands of parallel browser and device sessions.
• Own the data layer across PostgreSQL, ClickHouse, OpenSearch and Redis.
• Own delivery across the whole lifecycle: containerize with Docker, deploy and run on Kubernetes, automate with Ansible, and ensure the software runs reliably in customer environments you don't control.
• Solve hard problems end to end: find the bottleneck, profile it, design the fix, ship it and watch it in production.
• Ship features in React when the work needs it.
• Set technical direction through design docs, architecture reviews and prototypes, and make and explain hard trade-off calls.
• Make the team AI-native by using AI coding tools every day and helping shape how the team builds with them.

What you'll need

• Strong professional software engineering experience, with a strong record of building and owning complex backend systems.
• Deep expertise in Java or Go, including concurrency, memory management, performance tuning and idiomatic modern code.
• Hands-on experience building with LLMs, including RAG systems in production or close to it: embeddings, vector or hybrid search, chunking strategies, reranking and retrieval evaluation.
• Hands-on experience building with LLMs, including AI agents: tool and function calling, multi-step planning, memory and state, and handling failures and non-determinism.
• Prompt and context engineering, plus evaluation: knowing how to measure whether an LLM feature actually works.
• Daily, effective use of AI coding tools (Claude Code, Cursor, Copilot or similar).
• Strong computer science fundamentals and problem-solving ability, with the ability to reason about correctness, performance and distributed-systems trade-offs from first principles.
• Production experience with data stores: solid PostgreSQL skills plus hands-on experience with at least one of ClickHouse, OpenSearch/Elasticsearch or Redis at scale.
• Hands-on with Docker, Kubernetes and Ansible, having deployed, debugged and operated your own services.
• Working proficiency in React and modern frontend development.
• An owner's mindset, doing well with autonomy and ambiguity.
• Clear written communication, comfortable working remotely and asynchronously.

Nice to have

• Experience with MCP or agent frameworks.
• Experience with browser automation and test infrastructure: Selenium/WebDriver, Playwright, Appium, Selenium Grid, or device and emulator farms.
• Deeper Kubernetes knowledge: operators, custom controllers, autoscaling, or multi-tenant design.
• Experience with high-throughput ingestion and analytics, such as event pipelines, time-series data, or ClickHouse schema and materialized view design.
• Experience running self-hosted or open-weight LLMs (vLLM, Ollama, TGI) for air-gapped or data-sensitive deployments.
• Experience with fine-tuning, small-model distillation, or multimodal models (screenshots, DOM, visual diffing).
• Background building on-premise enterprise software for locked-down or regulated customer environments.
• Familiarity with security and compliance expectations in financial services or healthcare.

Details

• Remote, based in India.
• Fully remote, with a team that values deep work and written communication.
• Roughly 90% backend work in Java or Go and 10% frontend work in React.