Gen AI, Python Engineer (AI/LLM | FastAPI | AWS)

Position Description

Founded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 94,000 consultants and professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com.

Job Title: Gen AI, Python Engineer (AI/LLM FastAPI AWS)

Experience: 5 + Years

Location: Hyderabad/Bangalore/Chennai

Position ID : J0626-2473

At CGI, we are looking for a highly motivated and experienced Senior Software Engineer – Generative AI / Machine Learning to join our AI and Digital Engineering team. In this role, you will design, develop, and deploy enterprise-grade AI and Machine Learning solutions leveraging Large Language Models (LLMs), Python, and AWS cloud technologies.

You will collaborate with cross-functional teams to build scalable, secure, and production-ready AI applications that deliver measurable business value across diverse industry domains.

Your future duties and responsibilities

Design and develop scalable Machine Learning and Generative AI solutions for enterprise applications.

Build intelligent applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures.

Develop backend services, APIs, and AI workflows using Python.

Build and optimize prompt engineering strategies and LLM orchestration pipelines.

Develop and deploy AI/ML solutions on AWS using services such as Amazon Bedrock, SageMaker, Lambda, S3, EC2, API Gateway, and RDS.

Build scalable data ingestion, preprocessing, and feature engineering pipelines.

Deploy ML models using MLOps best practices and automate model lifecycle management.

Implement CI/CD pipelines for AI/ML applications.

Monitor production models for performance, scalability, latency, and model drift.

Design secure, scalable, and resilient AI architectures aligned with enterprise standards.

Collaborate with product owners, architects, data engineers, and development teams to integrate AI capabilities into business applications.

Stay current with emerging AI technologies, frameworks, and industry best practices, contributing to innovation initiatives and Proofs of Concept (PoCs).

Required Qualifications To Be Successful In This Role Must-Have Skills:

5–7 years of experience in software development with strong expertise in Python.

Hands-on experience in Machine Learning and Generative AI application development.

Experience building applications using Large Language Models (LLMs).

Strong understanding of:

Prompt Engineering

Retrieval-Augmented Generation (RAG)

Embeddings and Vector Search

Natural Language Processing (NLP)

Experience with Machine Learning frameworks such as:

PyTorch

TensorFlow

Scikit-learn

Experience with LLM orchestration frameworks such as LangChain or LlamaIndex.

Experience developing RESTful APIs using FastAPI or Flask.

Strong knowledge of SQL and NoSQL databases.

AWS & Cloud

Hands-on experience with AWS cloud services including:

Amazon Bedrock

Amazon SageMaker

AWS Lambda

Amazon S3

Amazon EC2

Amazon RDS

API Gateway

Experience deploying cloud-native AI applications.

Knowledge of cloud security, monitoring, and cost optimization.

Preferred Skills Experience with vector databases such as Pinecone, FAISS, OpenSearch, ChromaDB, or Weaviate.

Experience fine-tuning foundation models using PEFT or LoRA.

Knowledge of Responsible AI, AI governance, and model explainability.

Experience building enterprise-scale AI solutions in cloud environments.

Required Competencies

Strong analytical and problem-solving skills.

Excellent verbal and written communication skills.

Ability to work effectively in Agile development environments.

Strong collaboration and stakeholder management skills.

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