AI Engineer

We're Hiring: AI Engineer

Location: Pune (Kalyani Nagar)

Experience: 4-6 Years

Employment: Type: Full-Time

About Mphasis

At Mphasis, we leverage technology to deliver innovative solutions that help businesses accelerate their digital transformation journey. We are committed to creating a dynamic work environment that encourages innovation, learning, and career growth.

Key Responsibilities:

• Bachelor's or Master's degree in Computer Science, AI/ML, or Engineering, or equivalent practical experience.
• A strong track record of building and operating production backend systems at scale, including distributed services, APIs, async processing, data stores, and observability.
• Strong API design and integration experience: you know how to build services that other systems, and now LLMs, can call safely and reliably.
• Excellent Python engineering skills, including async programming, API development (FastAPI or similar), and microservices, plus SQL proficiency.
• Hands-on experience shipping at least one LLM-powered application to production that uses tool/function calling, such as agents that call APIs, query databases, or trigger workflows. This can be with OpenAI, Anthropic, Gemini, or open-source models.
• A working understanding of Gen AI engineering patterns, such as prompt design, embeddings, semantic search, and agent memory, or a demonstrated ability to ramp up quickly on new technical domains.
• Experience with at least one cloud platform (AWS preferred; Azure or GCP welcome).
• Experience leading or mentoring engineers, plus strong communication and stakeholder management skills. You should be able to translate technical work into business value.
• Nice to have: experience with Model Context Protocol (MCP) or building tool servers and connectors for LLM agents.
• Nice to have: experience evaluating agent performance, such as tool-selection accuracy, task completion rates, or multi-step reasoning reliability.
• Nice to have: exposure to fine-tuning (LoRA, PEFT, RLHF), multimodal models, knowledge graphs, or MLOps tooling like MLflow, Weights & Biases, SageMaker, or Bedrock.
• Coming from a backend background We value engineers who take AI from prototype to production as much as those who train the models. If you've built high-throughput systems and started applying those skills to LLM-powered products, we want to hear from you, even if you haven't worked with every tool listed here.

What We Offer:

Challenging projects with global clients

Learning and certification opportunities

Collaborative work culture

Career growth and development opportunities

Interested candidates can apply directly or share their profiles at [email/contact].