Part-Time Lead AI Engineer

1 day ago

Mumbai, Maharashtra, India Rearck Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Primary Responsibilities

  • Mentor and coach junior AI engineers through 1:1s, code reviews, pair programming, and structured learning plans
  • Provide hands-on technical leadership: solution design, architecture decisions, design docs, and best practices
  • Set coding standards and review PRs for quality, security, and performance
  • Lead the design and implementation of RAG pipelines: loaders, chunking, embeddings, vector stores, retrieval, reranking, and response synthesis
  • Guide the development of LLM agents with tool or function calling to interact with APIs and services
  • Oversee data engineering workloads: ingestion, transformation, orchestration, and reliability
  • Define evaluation, observability, and guardrails to reduce hallucinations and improve accuracy, latency, and cost
  • Collaborate with product, data, and platform teams; drive sprint planning and technical milestones
  • Document architecture, runbooks, and playbooks; enable knowledge transfer across the team

Required Skills and Experience

  • Proven experience leading or mentoring engineers on AI or data projects
  • Strong coding in Python and SQL; emphasis on readable, testable, maintainable code
  • Practical LangChain experience (chains, agents, tools, memory, callbacks) or equivalent frameworks such as LangGraph or LlamaIndex
  • Hands-on work with vector databases and embeddings (FAISS, Pinecone, Weaviate, Milvus; OpenAI or other embedding providers)
  • Experience building RAG systems and LLM agents in production or high-quality prototypes
  • Data engineering fundamentals: modeling, transformations, performance, and cost awareness
  • Comfortable with Git workflows, CI CD, and code review processes
  • Ability to work the stated US hours (8:00 PM12:00 AM IST), up to 4 hours per day

Nice to Have

  • Orchestration or transformation tools: Airflow, Dagster, dbt
  • Distributed data and storage: Spark or Databricks, Kafka, Delta Lake, Parquet; cloud data warehouses such as Snowflake, BigQuery, or Redshift
  • Cloud basics on AWS, Azure, or GCP; containers and CI CD: Docker, Kubernetes, GitHub Actions or GitLab CI
  • RAG and LLM evaluation and observability: RAGAS, Langfuse, MLflow, Weights and Biases, OpenTelemetry
  • Security practices: secret management, PII handling, prompt-injection defenses, rate limiting
  • Document processing: OCR and parsers for PDFs or HTML

Engagement Details

Type: Part-time (contract or consulting)

Hours: Up to 4 hours per day, 8:00 PM12:00 AM IST, aligned to US business hours

Duration: Initial part-time engagement with potential extension based on performance and need

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