AI Engineer/Forward Deploy Engineer

Location: Chennai, India (Hybrid)

Employment: 3-6 Month Contract to Hire

Team: AI Engineering & Operations

Reports To: AI Program Lead

Shift: 1:30PM IST - 9:30PM IST

Rate: 35LPA-45LPA

About the Opportunity

Our client is investing heavily in AI and is seeking an AI Engineer to help define how AI is built, deployed, and scaled across the organization.

This is not a traditional machine learning role where someone spends years focused on a single model or research initiative. The team is looking for a hands-on builder who can take an idea from concept to production, working across architecture, engineering, stakeholder engagement, and team leadership.

The environment is best described as a startup operating within a larger organization. The ideal candidate enjoys ambiguity, moves quickly, and is energized by solving new problems rather than maintaining existing systems. They are the type of engineer who experiments with emerging technologies, explores new frameworks on their own time, and stays plugged into the rapidly evolving AI ecosystem.

Success in this role requires equal parts technical depth and business acumen. This person will be expected to build and coach, while also serving as a trusted advisor to stakeholders across the business.

What We're Looking For

We're interested in engineers who have demonstrated an ability to build real-world AI solutions rather than simply consume AI tools.

The strongest candidates will have experience:

• Building AI applications that are actively used in production environments
• Translating business challenges into practical AI solutions
• Designing systems rather than simply contributing code
• Working in fast-paced startup, consulting, or innovation-focused environments
• Leading technical discussions and influencing engineering direction
• Mentoring other engineers and establishing best practices

This person should be comfortable moving between strategic conversations with leadership and highly technical implementation work with engineers. Day-to-Day Responsibilities

• Support the technical direction for AI initiatives across the organization
• Design scalable AI architectures and establish engineering standards
• Build and deploy AI-powered applications, agents, and automation solutions
• Partner with business stakeholders to identify opportunities where AI can create measurable value
• Define how AI solutions are evaluated, monitored, and improved over time
• Mentor engineers and help grow the overall maturity of the AI organization
• Guide build-versus-buy decisions related to AI platforms, models, and tooling
• Collaborate with global teams to turn concepts into production-ready solutions

Ideal Background The hiring team is particularly interested in professionals who have backgrounds such as:

• Early-stage startup engineers
• Founding or founding-team engineers
• AI consultants who have delivered multiple client solutions
• Technical founders or entrepreneurs
• Engineers who actively participate in hackathons, open-source projects, or AI communities
• Builders who have worked across a variety of AI use cases rather than one narrow specialty

Candidates who have spent their careers in highly structured enterprise environments without exposure to innovation-focused work may be less successful in this environment.

Technical Environment

While the team values problem-solving and engineering capability over keyword matching, successful candidates will likely have experience with many of the following areas:

• AI agents and agent orchestration
• Retrieval-Augmented Generation (RAG)
• LLM application development
• Prompt engineering and evaluation frameworks
• AI deployment and observability
• Model integrations and enterprise system connectivity
• Cloud-based AI platforms
• Python-based application development

Exposure to agent frameworks such as LangChain, LangGraph, CrewAI, Semantic Kernel, or similar technologies is beneficial. What Will Make Someone Stand Out The hiring manager is drawn to people who are genuinely excited by AI and continuously learning

Examples include

• Building side projects with AI outside of work
• Experimenting with open-source or open-weight models
• Sharing ideas within AI communities
• Contributing to open-source projects
• Participating in hackathons or technical competitions
• Demonstrating curiosity about emerging approaches to agentic AI

More than anything, this team wants someone who is a builder, can learn quickly, and is comfortable helping shape a growing AI function.