Note: The job is a remote job and is open to candidates in USA. Saransh Inc is hiring a Senior Python AI Engineer to operate and evolve the infrastructure for an enterprise knowledge base and agentic knowledge platform. The role focuses on building Python backend services, retrieval and agent runtime capabilities, ingestion pipelines, observability, evaluation workflows, and operational controls for AI-heavy workloads.
Responsibilities
- Architect and implement backend services in Python 3.11, FastAPI, Pydantic, SQLAlchemy async, and asyncpg
- Design retrieval and orchestration trade-offs around quality, latency, cost, safety, and operational simplicity
- Build production-grade agent runtime capabilities: memory boundaries, tool sandboxing, permissions, and budget controls
- Improve answer grounding, failure analysis, and citation enforcement rather than optimizing for demo behavior
- Create observability and operational feedback loops with OpenTelemetry, Prometheus/Grafana, Docker/Helm, and GitHub Actions
- Work closely with product and engineering partners to support multiple conversational surfaces through one knowledge platform
- Ingestion infrastructure across current and future content sources
- Observability across application, pipeline, database, and model-serving behavior
- Cost, latency, throughput, and failure-mode management for AI-heavy workloads
- Release workflows that validate AI behavior changes, not just code compilation
Skills
- 10+ years
- Strong hands-on experience with Python in platform, automation, or infrastructure-heavy environments
- Experience building CLI tools using Python, Golang or Rust
- Hands-on experience with LangGraph, LangChain, pgvector, and modern retrieval pipelines
- Experience designing evaluation frameworks for LLM-backed systems, including regression detection and quality measurement
- Strong experience with Docker, Helm, GitHub Actions, and Kubernetes-oriented workflows
- Familiarity with the operational characteristics of embedding pipelines, vector search, and LLM-backed systems
- Strong observability skills across metrics, tracing, dashboards, alerting, and log analysis
- Experience with ingestion, ETL, or content-processing pipelines at scale
- Ability to think in terms of reliability, cost, latency, throughput, and recovery
- Experience with Qdrant, Neo4j, or other vector/graph infrastructure
- Experience supporting RAG, search, evaluation, or agent platforms
- Experience in enterprise or regulated environments
- Familiarity with Vault, Splunk, Artifactory, ECR
- Comfort using AI-assisted engineering workflows in day-to-day work
Benefits
- Remote (US)
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