AI Full Stack Engineer

Job Description

We are looking for a AIFull Stack Engineer who operates effectively at the intersection of system analysis, enterprise integration and data engineering to support GenAI initiatives.

Key Responsibilities

1. System Analysis & Design

• Analyse business/technical requirements and translate them into data flows and integration designs
• Work with upstream and downstream teams to define data contracts and interfaces
• Identify gaps, inefficiencies and risks in current data movement processes
• Propose pragmatic solutions balancing speed, quality and maintainability

2. Integration & Data Movement

• Design and implement data movement across systems using:
• APIs
• SFTP and file based transfers
• Batch pipelines
• Coordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.)
• Ensure data is correctly transformed, mapped and delivered to target systems
• Troubleshoot integration issues across environments

3. Data Preparation for GenAI

Support data ingestion and preparation for GenAI use cases:

document ingestion

data aggregation

enrichment and transformation

Work with structured and unstructured data

Ensure data is usable for downstream AI workflows (RAG, search, investigation flows)

You are not asking them to build models, just make data usable for them.

4. Delivery & Coordination

Work across multiple teams:

data platforms

application teams

infrastructure

security

Support SIT, UAT and production rollouts

Ensure integration reliability, error handling and monitoring

Document flows, mappings and interfaces clearly

5. Production Support

Provide production support for deployed applications, including incident investigation, troubleshooting, resolution, and service restoration.

Perform bug fixes, code corrections, and application development changes required to resolve production issues and improve application stability.

Develop and implement enhancements or technical changes arising from production issues, operational requirements, or continuous improvement.

Troubleshoot issues across the full technology stack, including Python, Celery, database, Docker, Kubernetes/OpenShift, and CI/CD.

Requirements:

5-10 years of experience in system analysis, integration engineering, data engineering or technical delivery roles.

Good SQL and Python skills for data handling, scripting, automation and troubleshooting.

Good knowledge of front end stack, such as HTML, Jinja templating.

Experience with Celery for asynchronous / background task processing

Strong ability to translate requirements into system flows, data flows, interface specifications and implementation plans.

Experience working with upstream and downstream teams to define and deliver enterprise integrations.

Practical experience with REST APIs, SFTP, batch processing, file based integration and data pipeline orchestration.

Good understanding of data mapping, transformation, aggregation, reconciliation and data quality controls.

Exposure to Java

Exposure to Cloudera or similar enterprise data platforms.

Working knowledge of Git, branching, pull requests, code reviews and controlled release practices.

Familiarity with CI/CD, Jira, Confluence and enterprise deployment processes.

Experience of deploying and supporting application on Kubernetes and OpenShift (OCP)

Experience with Control M or equivalent scheduling tools.

Familiarity with logging and monitoring tools such as Splunk, Elastic Stack.

Exposure to GenAI concepts such as document ingestion, RAG, embeddings and data preparation for AI workflows.

Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams.

Key Domain/ Technical Skills

DevOps: CICD, Kubernetes/Openshift, Docker, Jenkins, Bash

Backend: Python, SQL, Celery, Gen AI prompting

Frontend: TypeScript, HTML, Jinja