EAIG:AI Solution Engineer

• Build conversational and agent-based applications
• Fine-tune and test models
• Design prompts and agent flows
• Rapidly prototype and iterate
• Collaborate closely with architects and business stakeholders.

Work Areas & Outcomes –

GenAI application development, experimentation, solution delivery

Optimal qualification for success on the job is:

• 5-8 years.

For successful execution of the job, the candidate should possess:

Capability & Skill Expectations –

• Hands-on data science skills applied to GenAI use cases, including model fine-tuning, prompt optimization, testing, and evaluation.
• Experience with LLMs, embeddings, retrieval, and agent-based architectures

Platform & Engineering Exposure –

• Experience applying COTS model-development and agent-development platforms to business use cases.
• Ability to integrate APIs, orchestration frameworks, vector databases, and enterprise data sources.

Observability & Evaluation Expectations –

Exposure to observability and evaluation for AI/agent-based apps, including prompt/version tracking, quality evaluation, latency and cost monitoring, hallucination analysis, and human-in-the-loop feedback.