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autonomize ai

Senior Software Development Engineer

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  • Posted 2 hours ago
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Early Applicant

Job Description

You'll architect and ship across the full Genesis stack: agentic pipelines, backend APIs, data infrastructure, and clinical-facing UI. You'll work directly with founders and customers. You'll own things end-to-end. This is not a role where you bolt AI onto existing CRUD. You'll be making foundational decisions about how intelligent systems are designed, evaluated, and operated at scale in a regulated industry.

The Core Requirements For The Job Include The Following

You build robust backend systems:

  • 6 + years building production web applications from scratch.
  • Deep Python proficiency; comfortable with FastAPI, Django, or Flask in production.
  • Experience designing APIs that serve both humans and AI agents (tool schemas, structured outputs, streaming).
  • Async-first thinking: asyncio, task queues, event-driven architectures.
  • Good to have Kafka, Redis, or ActiveMQ for real-time data movement.
  • Nice to have Postgres, Elasticsearch, MongoDB, or graph databases (Neo4j, TigerGraph) in production.

AI-native Engineering Is Your Default Mode

  • You've built production systems where LLMs are doing real work - not demos, not PoCs.
  • You've designed and shipped RAG pipelines, multi-agent workflows, or tool-using agents in production.
  • You understand prompt engineering as an engineering discipline: versioning, evaluation, and regression testing.
  • You've instrumented AI systems for observability - latency, token usage, hallucination rate, and drift.
  • You can reason about model tradeoffs (context length, cost, latency, accuracy) and make architectural calls accordingly.
  • You've worked with LLM SDKs (OpenAI, Anthropic, Bedrock, etc. ) and agentic orchestration frameworks (LangChain, LlamaIndex, CrewAI, or similar).

You Operate At Cloud Scale

  • Docker and Kubernetes in production - this is a hard requirement.
  • At least one public cloud (AWS, Azure, GCP) with real operational experience.
  • Microservices and cloud-native design patterns.
  • You've been on-call. You know what a bad deploy feels like at 2 am.
  • You can ship a frontend when the product demands it.
  • Nice to have React, TypeScript, or modern JS frameworks.
  • Enough frontend fluency to build clinical interfaces without a dedicated frontend handoff.

Bonus Points

  • Led a small engineering team - mentored, reviewed, unblocked.
  • CKAD or equivalent Kubernetes certification.
  • ML/DL model deployment experience (PyTorch, scikit-learn).
  • Built evaluation harnesses or used MLflow, LangSmith, or similar for AI observability.
  • Healthcare domain experience (FHIR, HL7 clinical workflows).

This job was posted by Daniya Mehak from Autonomize AI.

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About Company

Job ID: 147508329

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