Data Engineer

Simelabs - Digital, AI/ML, Automation, Robotics, Gen AI.; Ernakulam; On-site; INR 4,000,000 - 6,800,000; Full time

Job summary

Simelabs is seeking an AI Technical Lead / Principal Backend & AI Engineer to design and build enterprise-grade AI platforms, backend systems, and data-driven automation solutions. You will lead technical design, mentor teams, and deliver scalable AI-powered applications using Python, Generative AI, RAG, and cloud-native architectures.

The role requires 8–15 years of experience in backend engineering, AI, or data engineering, with strong leadership and hands-on delivery across distributed

Qualifications

• 8–15 years of experience in backend engineering, AI, or data engineering.
• Hands-on experience building enterprise AI solutions.
• Strong understanding of distributed systems, data architecture, and enterprise software development.

Responsibilities

• Design and implement enterprise AI applications using LLMs and microservices.
• Build RAG and semantic search solutions for enterprise knowledge retrieval.
• Lead technical design, architecture reviews, and mentoring of engineering teams.
• Develop scalable backend services and APIs with a focus on security and reliability.

Skills

Python

SQL

REST APIs

GraphQL

Generative AI

RAG

LangChain

LangGraph

Prompt Engineering

Vector Databases

Embeddings

OpenAI APIs

Agentic AI

dbt

ETL / ELT

Apache Spark / PySpark

AWS

Elasticsearch/OpenSearch

Docker

Git

CI/CD

Airflow

Tools

Docker

Airflow

Job description

AI Technical Lead / Principal Backend & AI Engineer

Experience: 8-15 Years

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.
• Design prompt engineering strategies and AI evaluation pipelines.
• Build semantic search using vector databases and embeddings.
• Design AI APIs and enterprise AI integrations.
• 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.
• 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.
• Design cloud-native applications on AWS.
• 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.
• 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
• REST APIs
• GraphQL (preferred)

AI & GenAI

• Generative AI
• RAG
• LangChain
• LangGraph
• Prompt Engineering
• Vector Databases
• Embeddings
• OpenAI APIs (or equivalent)
• Agentic AI
• dbt
• ETL / ELT
• Apache Spark / PySpark (preferred)

AWS

• AWS Lambda
• S3
• Glue
• Redshift
• EC2

Databases

• Amazon Redshift
• MySQL
• Redis

Search Technologies

• Elasticsearch/OpenSearch
• Kibana

DevOps

• Docker
• Git
• CI/CD

Good to Have

• CrewAI
• AutoGen
• OpenTelemetry
• Grafana
• 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.
• Strong understanding of distributed systems, data architecture, and enterprise software development.
• Excellent communication and stakeholder management skills.