AI Engineer

About the job

The GenAI Engineer / Developer is responsible for designing, building, and deploying enterprise‑grade Generative AI applications that accelerate digital transformation across the business. This role focuses on hands‑on engineering of LLM‑powered systems, including copilots, RAG solutions, agentic workflows, and AI‑driven automations tailored to local business needs.

The position plays a critical role in translating business problems into scalable, secure, and production‑ready GenAI solutions. Working closely with cross‑functional stakeholders—Sales, HR, Operations, Finance, and IT—the GenAI Engineer rapidly prototypes, iterates, and operationalizes AI solutions that deliver measurable business impact.

A key accountability of the role is ensuring quality, safety, performance, and trust of GenAI systems through robust prompt design, grounding strategies, guardrails, evaluation frameworks, and LLMOps practices. The role also contributes to building sustainable internal AI capability by developing reusable components, reference architecture, documentation, and best practices.

This position is critical for enabling parallel GenAI workstreams, reducing delivery bottlenecks, and establishing long‑term, in‑house expertise to support enterprise‑wide GenAI scaling.

Position Responsibilities:

• Design, build, and deploy end‑to‑end Generative AI applications, including LLM‑based copilots, chatbots, RAG pipelines, multi‑agent systems, and multimodal workflows.
• Develop and optimize retrieval‑augmented generation (RAG) solutions using vector databases, embeddings, metadata filtering, and grounding techniques to ensure accurate and context‑aware outputs.
• Implement prompt engineering, tool/function calling, and agent orchestration to enable reliable task execution and workflow automation.
• Integrate GenAI solutions with enterprise systems and data sources via APIs, event‑driven architectures, and secure connectors.
• Collaborate with product owners and business stakeholders to translate requirements into technical architectures and implementation plans.
• Establish and follow best practices for LLMOps, including deployment pipelines, monitoring, logging, evaluation, cost optimization, and performance tuning.
• Implement AI safety, governance, and guardrails, including content filtering, grounding validation, access control, and compliance requirements.
• Continuously evaluate emerging GenAI models, frameworks, and tooling to improve solution quality, latency, and cost efficiency.
• Contribute to internal capability building by creating reusable libraries, templates, documentation, and reference implementations.

Required Qualifications

• 3–5 years of experience in software engineering, AI engineering, ML engineering, or related fields.
• At least 1 year of hands‑on Generative AI development experience, building and deploying LLM‑based applications.
• Strong proficiency in Python and experience developing APIs and backend services.
• Practical experience with LLMs, embeddings, vector databases, and RAG architecture.
• Familiarity with GenAI frameworks such as LangChain, Semantic Kernel, LlamaIndex, or similar.
• Experience working with cloud AI platforms (Azure, Databricks, NVIDIA, or equivalent).
• Bachelor’s degree in computer science, Computer Engineering, Information Technology, Artificial Intelligence, or related disciplines.

Relevant Certifications (at least one preferred):

• Databricks Certified Generative Engineering Associate
• Databricks Certified ML Associate / Professional
• Microsoft Generative AI Engineering Professional Certificate
• Microsoft Certified: Azure AI Engineer Associate
• NVIDIA Generative AI / LLMs Certified Associate
• IBM Generative AI Engineering Professional Certificate

Preferred Qualifications

• Master’s degree or PhD in Computer Science, AI, Electrical Engineering, Physics, or related fields.
• 4+ years of experience in AI, ML, or software engineering roles.
• Proven experience delivering production‑grade GenAI solutions in enterprise environments.
• Experience with LLMOps, MLOps, CI/CD, and cloud‑native architectures.
• Databricks Certified Generative Engineering Associate or Microsoft Generative AI Engineering Professional Certificate.

When you join our team:

• We’ll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part…