SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Nexla is a leading AI-native data integration platform trusted by companies like DoorDash, LinkedIn, and Johnson & Johnson. The platform processes 500+ billion rows daily and is being rebuilt around AI-native connectors, distributed Python runtimes (Ray), and LLM-powered data workflows.
As a Software Engineer, you will own core platform development across the full stack. Your primary focus (70%) will be building AI-native connectors that blend traditional integration primitives—pagination, schema evolution, rate-limiting, retries—with LLM-driven capabilities like semantic understanding, agentic recovery, and natural-language tool design. You'll work directly with production LLMs, designing prompts, tool schemas, evaluation harnesses, and guardrails.
Key responsibilities include:
- Implementing intelligent connectors with end-to-end ownership from design to deployment
- Working with distributed Python runtimes (Ray, Arrow, Polars, DuckDB) to optimize throughput, latency, and cost
- Building self-recovery mechanisms and agentic probes to handle messy, real-world data at scale
- Moving fluidly across backend services, runtime code, agent orchestration, and frontend as needed
- Collaborating with the CTO and senior leads on architectural decisions for multi-tenancy and AI-native workflows
- Writing documentation and RFCs to enable the platform and customers to build on your work
You should have 2–5 years of software engineering experience with strong polyglot fluency in at least one modern backend language (Python, Java, Kotlin, Scala, C++, Go, Rust). Full-stack capability is essential—you're comfortable across backend, data/runtime, and frontend or infrastructure. You have solid CS fundamentals (data structures, algorithms, concurrency, distributed systems) and operate with high agency, urgency, and ownership. Demonstrated builder spirit (GitHub projects, open-source, technical blog) and hands-on experience with AI tools (Claude Code, Cursor, agentic workflows) are expected. You can overlap with evening PST hours for collaboration with India and Europe-based teams.
Nice-to-haves include experience with Ray, Arrow, Polars, DuckDB, or hands-on LLM work (RAG pipelines, agentic systems, function calling, evals, MCP servers).
