Framework Engineer

2 weeks ago


Bengaluru, India Lyzr AI Full time

About the roleLyzr is hiring a hands-on framework engineer to build the core primitives that power agent orchestration and Retrieval-Augmented Generation (RAG) at enterprise scale. You’ll design and ship SDKs, execution engines, and graph/DAG orchestrators used by thousands of agents in production. If you love clean APIs, concurrency, and building frameworks others love to build on, we should talk.What you’ll doDesign and implement core framework building blocks: nodes/operators, state stores, executors, schedulers, and adapters.Build orchestration managers (workflow, DAG, event-driven/manager-worker) with strong typing, retries, idempotency, and back-pressure.Develop RAG frameworks (indexing, chunking, embeddings, routing, re-ranking, Graph/GraphRAG patterns) with pluggable backends.Create integration layers and adapters for popular ecosystems (e.g., LangChain, LangGraph) and improve or replace them where needed.Drive performance & reliability: async/concurrency (asyncio), caching, vector I/O, tracing/telemetry, and low-latency streaming.Establish testing & release discipline: benchmarks, fuzz tests, contract tests, semantic versioning, docs, examples, and CI.Collaborate with product and solutions teams to turn real-world requirements into elegant public APIs and reference implementations.Must-have qualifications5+ years building developer frameworks, SDKs, or distributed systems in Python (3.10+); strong API design and packaging discipline.Deep experience with workflow/DAG orchestration and stateful systems (schedulers, retries, checkpoints, resumability).Proven RAG foundation: vector stores, retrieval strategies, evaluation harnesses, hybrid search, and graph/GraphRAG concepts.Strong async/concurrency skills (asyncio), profiling, and performance tuning.Excellent testing habits (unit/integration/property tests), doc culture, and empathy for downstream developers.Nice to have (big plus)Rust for performance-critical components (ownership/borrowing, async runtimes like tokio).Prior work on/with LangChain, LangGraph, CrewAI, LlamaIndex, or similar—either contributions or deep adapter/internal use.Graph databases/engines (Neo4j, Memgraph), vector DBs (pgvector, Pinecone, Weaviate, Milvus), message buses (Kafka, NATS).Observability & safety: OpenTelemetry tracing, eval harnesses, red-team pipelines, guardrails/hallucination mitigation.Systems patterns: plugin architectures, dependency injection, DSLs, CRDTs/state machines, event sourcing.Cloud/K8s familiarity and secure on-prem/VPC deployments.What we valueBuilder energy: you can write a framework from scratch or improve an existing one with restraint and taste.Pragmatism over hype: small, composable pieces; stable APIs; sharp boundaries.OSS spirit: code readability, docs, examples, and community stewardship.What to include with your applicationLinks to GitHub (or equivalent), notable PRs/issues, PyPI/crates.io packages, talks, or design docs.Short note on a framework you built/improved: the API choices you made and why.Apply Here: https://lyzr.notion.site/2a140f4a0e9a80bbb49af43fbc251e19?pvs=105


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