AI Full Stack Engineer
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Summary
Engineer working at the intersection of system analysis, enterprise integration and data engineering to support GenAI initiatives: designing data flows and integrations (APIs, SFTP, batch pipelines), preparing structured/unstructured data for RAG and AI workflows, and providing production support across a Python, Celery, Docker, Kubernetes/OpenShift stack.
Job Description
We are looking for a
AI
Full 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
AI
Full 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