Artificial Intelligence Engineer

Akkodis; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Akkodis is seeking an experienced AI/ML engineer in India to deliver production-ready AI/ML and LLM-based solutions. You will collaborate with product managers, data scientists, and engineers across locations to deploy models, build pipelines, and implement RAG/vector search techniques.

The role requires hands-on experience with GCP/Vertex AI, strong Python API skills, and a solid understanding of LLMs, security, and MLOps practices.

Qualifications

• Hands-on delivery of AI/ML or LLM-based solutions into production.
• Practical experience on GCP and Vertex AI, including deploying models and building pipelines.
• Solid understanding of LLMs, transformers, tokenization and RAG approaches.
• Experience building agentic AI workflows or AI agents.
• Knowledge of security and safety for AI systems, prompt/tool design, and data protection.
• Experience with CI/CD, version control, automated testing, IaC, monitoring in cloud environments.
• Strong Python skills and API development experience.
• Ability to design evaluations for AI features including human-in-the-loop where needed.
• Strong problem-solving skills and ownership mindset.
• Clear communication and collaboration with product managers, data scientists, and engineers across locations.

Skills

Production AI/ML delivery

GCP/Vertex AI

LLMs/Fndtn models

Agentic workflows

AI security

MLOps/DevOps

Python APIs

Experimentation/evaluation

Problem solving

Cross-functional collaboration

Tools

Git

Job description

• Strong experience in software/data/ML engineering, with hands‑on delivery of AI/ML or LLM‑based solutions into production (not just prototypes).
• Practical experience on GCP and Vertex AI, including deploying models, building pipelines, and implementing RAG/vector search‑based solutions.
• Solid understanding of LLMs and foundation models: transformers at a high level, tokenization, embeddings, context windows, RAG, and the trade‑offs between fine‑tuning, adapters and prompt‑based approaches.
• Hands‑on experience building agentic workflows or AI agents (e.g. tool‑augmented chat, multi‑step workflows, or multi‑agent systems) using one or more modern frameworks or platforms.
• Good grasp of security and safety for AI systems, including prompt and tool design to reduce hallucinations and prompt injection, safe handling of sensitive data, and application‑level guardrails.
• Experience with DevOps/MLOps practices: CI/CD, version control, automated testing, infrastructure as code, monitoring and incident handling in a cloud environment.
• Strong programming skills in Python and experience building and consuming APIs; familiarity with microservices and event‑driven architectures is a plus.
• Ability to design and run evaluation and experimentation for AI features, including quantitative and qualitative measures and, where appropriate, human‑in‑the‑loop review.
• Strong problem‑solving skills, attention to detail, and a willingness to take ownership of complex technical challenges.
• Clear, proactive communication and the ability to collaborate effectively with product managers, data scientists, engineers and commercial stakeholders across locations.