Generative AI Engineer

Job Title:

Location:

Tech Stack:

Job Summary

strategic and hands-on GenAI Solution Architect

Key Responsibilities

Solution Design & Evaluation

• Architect end-to-end GenAI solutions for R&D use cases such as

  formulation assistance, scientific literature summarization, and regulatory compliance

  .
• Evaluate multiple solution approaches (e.g.,

  fine-tuning vs. RAG

  ,

  cloud-native vs. hybrid deployment

  ) and recommend optimal paths based on

  scalability, cost, and data sensitivity

  .
• Document architectural decisions with

  rationale, trade-offs, and risk assessments

  .
• Handle diverse data sources:

  Word, Excel, PDF, databases, audio, video, structured & unstructured data

  .
• Provide POV on implementing use cases via

  Agentic AI

  .

Technology Stack Selection

• Select and justify GenAI frameworks (e.g.,

  OpenAI, Azure OpenAI, Hugging Face Transformers, LangChain

  ) based on

  use case fit, latency, cost, and integration capabilities

  .
• Recommend cloud platforms (

  Azure

  ) and orchestration tools (e.g.,

  Kubernetes, Airflow

  ) for scalable deployment.
• Ensure compatibility with enterprise systems like

  SAP PLM, LIMS, and SharePoint

  .

Edge Case Handling & Robustness

• Identify and address edge cases such as

  ambiguous queries, hallucinations, data sparsity, and multilingual inputs

  .
• Implement

  fallback mechanisms, confidence scoring, and human-in-the-loop workflows

  .
• Design

  monitoring and feedback loops

  to continuously improve model performance and reliability.

Stakeholder Engagement

• Collaborate with

  R&D scientists, IT teams, and business leaders

  to align solutions with strategic goals.
• Lead workshops to

  gather requirements, validate prototypes, and drive adoption

  .
• Communicate complex AI concepts in

  business-friendly language

  .

Governance & Compliance

• Ensure solutions adhere to

  data governance, privacy, and regulatory standards

  .
• Define

  model auditability, explainability, and ethical AI practices

  .

Innovation & Capability Building

• Stay current with

  GenAI advancements and emerging tools

  .
• Mentor teams on

  prompt engineering, LLM fine-tuning, and responsible AI

  .
• Contribute to

  internal knowledge bases and reusable solution assets

  .

Required Qualifications

• 10+ years

  in solution architecture, with

  3+ years in AI/ML

  and

  2+ years in GenAI

  .
• Proven experience in

  evaluating and implementing GenAI solutions in enterprise settings

  .
• Strong understanding of

  LLMs, RAG, prompt engineering, and model deployment

  .
• Experience in

  FMCG, life sciences, or R&D domains

  preferred.
• Proficiency in

  Python, cloud platforms, and ML frameworks

  .
• Excellent

  analytical, communication, and stakeholder management skills

  .

• Bachelor’s/Master’s

  in Computer Science, Engineering, or related field.

If you fine this relevant, please email me your details along with your updated CV - Jonathan.mishael@ltimindtree.com