Data Engineer

Simelabs - Digital, AI/ML, Automation, Robotics, Gen AI.; Ernakulam; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Simelabs - Digital, AI/ML, Automation, Robotics, Gen AI. Kochi, India, seeks an AI Technical Lead to design and build enterprise AI platforms, backend systems, and data-driven automation solutions.

The role requires strong expertise in Python backend development, Generative AI, and cloud-native architectures, with responsibility for technical design and mentoring engineering teams.

Qualifications

• Strong Python backend development experience.
• Experience with Generative AI and LLMs.
• Cloud-native architectures and data engineering exposure.

Responsibilities

• Design and lead enterprise AI platforms and backend systems.
• Mentor engineering teams and drive technical design.
• Deliver scalable AI-powered enterprise applications.

Skills

Python

SQL

Docker

REST APIs

LLMs

RAG

Education

Bachelor's degree

Tools

Airflow

dbt

Spark/PySpark

Job description

AI Technical Lead / Principal Backend & AI Engineer

Experience: 8-15 Years

Location: Kochi

Employment Type: Full-Time

Role Summary

We are seeking an experienced AI Technical Lead to design and build enterprise-grade AI platforms, backend systems, and data-driven automation solutions. The ideal candidate should have strong expertise in Python backend development, Generative AI, Agentic AI, cloud-native architectures, and data engineering. The role involves leading technical design, mentoring engineering teams, and delivering scalable AI-powered enterprise applications.

Key Responsibilities

AI & Generative AI

• Design and implement enterprise AI applications using LLMs.
• Build Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge retrieval.
• Develop Agentic AI workflows using orchestration frameworks.
• Integrate OpenAI, Azure OpenAI, Claude, Gemini, or similar LLM services.
• Design prompt engineering strategies and AI evaluation pipelines.
• Build semantic search using vector databases and embeddings.
• Design AI APIs and enterprise AI integrations.

Backend Engineering

• Design scalable backend applications using Python.
• Build RESTful APIs and enterprise backend services.
• Develop distributed systems and microservices.
• Implement secure authentication and authorization.
• Design reusable and maintainable backend architecture.
• Perform architecture reviews and technical mentoring.

Data Engineering

• Build scalable ETL/ELT pipelines.
• Design workflow orchestration pipelines using Apache Airflow or equivalent.
• Develop data transformation pipelines using dbt or similar frameworks.
• Design operational and analytical data models.
• Work with structured and semi-structured enterprise datasets.
• Optimize large-scale data processing workloads.

Cloud & Platform Engineering

• Design cloud-native applications on AWS.
• Build scalable data pipelines using AWS services.
• Implement monitoring, logging, and automation.
• Containerize applications using Docker.
• Deploy applications using CI/CD pipelines.
• Ensure security, scalability, and high availability.

Search & Knowledge Systems

• Build enterprise search platforms.
• Design semantic search and hybrid search solutions.
• Implement Elasticsearch/OpenSearch.
• Optimize indexing and retrieval performance.
• Design enterprise knowledge repositories.

Leadership

• Lead technical teams and mentor engineers.
• Participate in architecture discussions and solution design.
• Review code and technical documentation.
• Collaborate with stakeholders and business teams.
• Drive engineering best practices and delivery excellence.

Required Technical Skills

Programming

• Python
• SQL

Backend

• Django / FastAPI / Flask
• REST APIs
• GraphQL (preferred)
• Microservices Architecture

AI & GenAI

• Generative AI
• Large Language Models (LLMs)
• RAG
• LangChain
• LangGraph
• Prompt Engineering
• Vector Databases
• Embeddings
• OpenAI APIs (or equivalent)
• Agentic AI

Data Engineering

• Apache Airflow
• dbt
• ETL / ELT
• Data Pipelines
• Apache Spark / PySpark (preferred)

AWS

• AWS Lambda
• S3
• Glue
• Redshift
• Athena
• EC2

Databases

• PostgreSQL
• Amazon Redshift
• MySQL
• Redis
• Cassandra (preferred)

Search Technologies

• Elasticsearch/OpenSearch
• Kibana
• Logstash
• Apache Solr (preferred)

DevOps

• Docker
• Git
• CI/CD
• Linux

Good to Have

• MCP (Model Context Protocol)
• CrewAI
• AutoGen
• OpenTelemetry
• Grafana
• Kafka / RabbitMQ
• Celery
• GCP (BigQuery, Dataflow)
• AI Observability
• AI Guardrails

Preferred Candidate

• 8–15 years of experience in backend engineering, AI, or data engineering.
• Strong experience leading engineering teams.
• Hands‑on experience building enterprise AI solutions.
• Experience designing scalable cloud-native platforms.
• Strong understanding of distributed systems, data architecture, and enterprise software development.
• Excellent communication and stakeholder management skills.