Gen AI Engineer
Full Time
full time
5 Aug 2025
Verified by Turrior
Content + Source + Freshness • 12 Dec 2025 • 95% confidence
87 / 100
Offer value
Outstanding value due to the niche skill set required in generative AI, potential for innovation, and relevance in modern tech solutions.
- Work in a highly innovative and growing AI field.
- Potential for real-world impact through generative technology.
- Role requires a comprehensive understanding of AI systems.
- Ample opportunities for professional development.
Pros
- Opportunity to work in a cutting-edge technology area.
- Potential for substantial impact through innovation.
- Demand for generative AI skills continues to rise.
Cons
- Requires deep technical knowledge and hands-on experience.
- Fast-paced environment may be demanding.
- Independence in driving projects may lead to pressure.
Who it's for
Mid-Level • On-site
Good fit
- Mid-level engineers experienced in AI or ML.
- Innovative thinkers eager to work with cutting-edge technology.
- Professionals looking to drive AI application development.
Not recommended for
- Novices in AI or software engineering.
- Individuals who prefer routine tasks over innovation.
- Candidates lacking independent project management skills.
Motivation fit
Passion for exploring innovative AI solutions.Interest in developing practical applications from prototypes.Aiming to contribute to groundbreaking technology projects.
Key skills
Generative AI knowledgeSoftware developmentPrototyping and experimentationCommunication and presentation
Score: 87/100 AI verified analysis
About the job
About the Role
We are seeking a Generative AI Engineer with 6–9 years of experience who can independently explore, prototype, and present the art of the possible using LLMs, agentic frameworks, and emerging Gen AI techniques. This role combines deep technical hands-on development with non-technical influence and presentation skills.
You will contribute to key Gen AI innovation initiatives, help define new protocols (like MCP and A2A) and deliver fully functional prototypes that push the boundaries of enterprise AI — not just in Jupyter notebooks, but as real applications ready for production exploration.
Key Responsibilities
LLM Applications & Agentic Frameworks
- Design and implement end-to-end LLM applications using OpenAI, Claude, Mistral, Gemini, or LLaMA on AWS, Databricks, Azure or GCP.
- Build intelligent, autonomous agents using LangGraph, AutoGen, LlamaIndex, Crew.ai, or custom frameworks.
- Develop Multi Model, Multi Agent, Retrieval-Augmented Generation (RAG) applications with secure context embedding and tracing with reports.
- Rapidly explore and showcase the art of the possible through functional, demonstrable POCs
- Fine-tune LLMs and Small Language Models (SLMs) for domain-specific use.
- Create and leverage synthetic datasets to simulate edge cases and scale training.
- Evaluate agents using custom agent evaluation frameworks (success rates, latency, reliability)
- Evaluate emerging agent communication standards — A2A (Agent-to-Agent) and MCP (Model Context Protocol)
- Translate ambiguous requirements into structured, AI-enabled solutions.
- Clearly communicate and present ideas, outcomes, and system behaviors to technical and non-technical stakeholders
- 6–9 years of experience in software development or AI/ML engineering
- At least 3 years working with LLMs, GenAI applications, or agentic frameworks.
- Proficient in AI/ML, MLOps concepts, Python, embeddings, prompt engineering, and model orchestration
- Proven track record of developing functional AI prototypes beyond notebooks.
- Strong presentation and storytelling skills to clearly convey GenAI concepts and value.
- Ability to independently drive AI experiments from ideation to working demo.
