The Role
Designs, builds, and scales generative AI agents and applications using LLMs, RAG, agentic frameworks, vector databases, and multimodal models. Responsibilities include architecture, model integration and fine-tuning, tool orchestration, cloud deployment, observability, evaluation, performance optimization, and cross-functional collaboration. The role also mentors engineers and advances production-grade AI platforms and workflows.
Summary Generated by Built In
We are looking for a passionate and experienced Generative AI Engineer to design, implement, and scale intelligent AI agents and applications. You will work on architecting agentic systems powered by LLMs, retrieval-augmented generation (RAG), and reasoning frameworks. The ideal candidate is someone who stays current with the fast-evolving GenAI ecosystem and can transform advanced research into production-grade solutions.
Key Responsibilities
- Architect, build, and deploy agentic AI systems using frameworks such as LangGraph, Google ADK,Autogen, Semantic Kernel, CrewAI, and LangChain.
- Design and implement RAG pipelines leveraging vector databases (OpenSearch, Pinecone, FAISS, or Weaviate).
- Develop modular and reusable AI agent architectures for dynamic reasoning and tool orchestration.
- Integrate and fine-tune foundation models (GPT, Claude, Gemini, Mistral, Llama, etc.) for domain-specific tasks.
- Work with APIs, embeddings, and context optimization for large-scale AI workflows.
- Collaborate with platform, data, and product teams to ensure robust integration and deployment.
- Implement observability, performance tracking, and continuous evaluation of model and agent behavior.
- Stay up to date with the latest research and open-source developments in LLMs, agents, and cognitive frameworks.
- Mentor and guide junior engineers on prompt design, agent architecture, and optimization techniques.
Required Skills & Experience
- 5–10 years of total experience in AI / ML engineering, including at least 2 years in Generative AI.
- Proven expertise with agentic frameworks — LangGraph, Google ADK, Semantic Kernel, CrewAI, LangChain, or similar.
- Strong programming skills in Python and familiarity with microservice or API-based systems.
- Hands-on experience with LLMs, vector search, and retrieval-augmented generation ( ) architectures.
- Good understanding of prompt engineering, model evaluation, and context optimization.
- Experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments.
- Exposure to model fine-tuning, LoRA, or custom embedding generation.
- Build multimodal content generation workflows:
Text → Image (Stable Diffusion, Runway, Sora, GPT, Midjourney APIs)
Image → Image / Video (image transformation, video synthesis)
Text → Video (Veo, Sora, Pika Labs, Runway ML, or similar)
Text → Audio / Speech (TTS systems, diffusion-based audio models)
Good to Have
- Knowledge of multimodal AI (text, image, audio, video).
- Experience building or contributing to internal agent SDKs and AI developer platforms.
- Understanding of tool-augmented reasoning, graph-based agent workflows, and memory architectures.
- Familiarity with data governance, hallucination control, and AI safety best practices.
- Experience optimizing inference latency and cost for production-scale models.
Soft Skills
- Strong problem-solving and analytical thinking abilities.
- Excellent communication and cross-functional collaboration skills.
- Self-driven, with a focus on ownership and innovation.
- Ability to translate complex technical ideas into practical, scalable implementations.
Why Join Us
- Work at the forefront of agentic and generative AI innovation.
- Collaborate with a highly skilled AI research and engineering team.
- Shape the architecture of next-generation intelligent systems.
- Opportunity to lead high-impact projects with cutting-edge LLM and reasoning frameworks.
- Competitive compensation, flexible work setup, and a culture centered on innovation and technical excellence.
Skills Required
- 5-10 years of experience in AI or machine learning engineering
- At least 2 years of experience in generative AI
- Expertise with agentic frameworks such as LangGraph, Google ADK, Semantic Kernel, CrewAI, LangChain, or similar
- Strong Python programming skills
- Familiarity with microservice or API-based systems
- Hands-on experience with LLMs, vector search, and retrieval-augmented generation architectures
- Understanding of prompt engineering, model evaluation, and context optimization
- Experience with AWS, Azure, or GCP
- Experience with containerized deployments
- Exposure to model fine-tuning, LoRA, or custom embedding generation
- Experience building multimodal content generation workflows involving text, images, video, audio, or speech
- Knowledge of multimodal AI
- Experience contributing to internal agent SDKs or AI developer platforms
- Understanding of tool-augmented reasoning, graph-based agent workflows, and memory architectures
- Familiarity with data governance, hallucination control, and AI safety practices
- Experience optimizing inference latency and cost for production-scale models
- Strong problem-solving, analytical, communication, collaboration, ownership, and innovation skills
- Ability to translate complex technical ideas into practical, scalable implementations
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The Company
What We Do
BRAHMA AI is an enterprise AI content platform that enables organizations to create, manage, and distribute AI-driven media with intelligence, security, and efficiency. Formed through the integration of Prime Focus Technologies and Metaphysic, it combines CLEAR®, CLEAR® AI, ATMAN digital humans, and VAANI voice localization into one ecosystem. Guided by its Mind² philosophy, BRAHMA AI helps enterprises scale content creation, protect IP, and govern assets with provenance, consent, and trust.
