About this role
Enterprises struggle to deploy dependable autonomous AI agents and scalable cloud-native SaaS platforms within complex industrial environments without robust architectural standards. To solve this challenge, Coforge seeks a Senior Full Stack AI Engineer with solution architecture experience to design and build resilient, high-performance systems for heavy industries. This practitioner will lead technical roadmaps, drive the adoption of generative and agentic AI, and write production-grade code while collaborating closely with product, sales, and engineering teams.
The ideal candidate brings extensive background in building cloud-native microservices, orchestrating LLM workflows, and shaping enterprise data models across SQL and NoSQL storage. Someone who thrives in a highly technical, hands-on environment and communicates well in advanced English will succeed in guiding engineering groups through complex transformations.
What you will do
- Design and build autonomous AI agents utilizing frameworks like LangGraph, LangChain, AutoGen, and CrewAI.
- Develop advanced Graph-RAG architectures that combine semantic search with structured knowledge retrieval.
- Implement production safeguards to ensure the traceability, reliability, security, and accuracy of AI outputs.
- Create high-performance Python APIs using FastAPI to power backend integrations and frontend applications.
- Define architectural standards and technical roadmaps for scalable SaaS platforms based on microservices.
- Architect cloud-native solutions on Azure or AWS using Docker, Kubernetes, Terraform, and Ansible.
- Partner with product, sales, customer success, and engineering groups to align technical delivery with business objectives.
What you need
- Hold a Bachelor's degree in Computer Science, Engineering, or a related STEM field.
- Demonstrate at least 8 years of professional engineering experience with enterprise applications.
- Bring proven expertise in AI and machine learning frameworks including LangChain, LangGraph, AutoGen, or CrewAI.
- Have hands-on experience deploying generative AI and agentic AI solutions in production environments.
- Possess strong technical proficiency in Azure or AWS cloud platforms alongside containerization tools like Docker and Kubernetes.
- Show deep familiarity with Infrastructure as Code using Terraform and Ansible.
- Maintain a strong understanding of both SQL and NoSQL databases alongside Python, Node.js, or React.
- Demonstrate advanced English proficiency and strong communication skills.
Nice to have
- Strong frontend development experience using React
- Experience within the Energy, Oil & Gas, or Industrial sectors
- AI-focused certifications and technical training, including Claude Code Architect or similar credentials
- Experience implementing enterprise-level AI governance and responsible AI practices
- Exposure to large-scale cloud transformation initiatives
Skills and tech stack
Questions candidates ask
What is the work location and mode for this role?
The position is based in Latin America and operates on a remote mode.
What kind of systems and architecture will I be working on?
You will design and build scalable, cloud-native SaaS platforms for complex industrial environments using a microservices architecture. The role also involves developing generative AI and autonomous agent solutions.
What core technologies and cloud providers are required?
The tech stack includes Python, Node.js, React, LangChain, LangGraph, Azure, AWS, Docker, Kubernetes, Terraform, and Ansible. You must also have strong experience with SQL and NoSQL databases.
Who will I collaborate with in this position?
You will partner with product, sales, customer success, and engineering teams to align business and technical objectives. The role also requires guiding engineering teams on architecture and design decisions.