Role & responsibilities
Key Skills required :
Generative AI, Multi Modal AI
Creative AI solutions and workflows across all creative content types including Copy/Text, Imagery, Key Visuals, Characters, Avatars, Audio, Speech and Video AI
Creative AI Automation workflows with content creation and content editing at scale, using AI services and AI APIs
Experience with multiple Multi Modal AI Foundation Models
LLM, LLM App Dev
AI Agents, Agentic AI Workflows
Responsibilities
- Design and build web apps and solutions that leverage Creative AI Services, Multi Modal AI models, and Generative AI workflows
- Leverage Multi modal AI capabilities supporting all content types and modalities, including text, imagery, audio, speech and video
- Build creative automation workflows that help produce creative concepts, creative production deliverables, and integrated creative outputs, leveraging AI and Gen-AI models
- Integrate AI Image Gen Models and AI Image Editing models from key technology partners
- Integrate Text / Copy Gen Models for key LLM providers
- Integrate Speech / Audio Gen and Editing models for use cases such as transcription, translation, and AI generated audio narration
- Integrate AI enabled Video Gen and Video Editing models
- Fine-Tune Multi Modal AI models for brand specific usage and branded content generation
- Constantly Research and explore emerging trends and techniques in the field of generative AI and LLMs to stay at the forefront of innovation.
- Drive product development and delivery within tight timelines
- Collaborate with full-stack developers, engineers, and quality engineers, to develop and integrate solutions into existing enterprise products.
- Collaborate with technology leaders and cross-functional teams to develop and validate client requirements and rapidly translate them into working solutions.
- Develop, implement and optimize scalable AI-enabled products
- Integrate Gen-AI and Multi Modal AI solutions into Cloud Platforms, Cloud Native Apps, and custom Web Apps
- Execute implementation across all layers of the application stack including front-end, back-end, APIs, data and AI services
- Build enterprise products and full-stack applications on the MERN + Python stack, with a clear separation of concerns across layers
Skills and Competencies:
- Deep Hands-on Experience in Multi modal AI models and tools.
- Hands-on Experience in API integration with AI services
- Multi Modal AI – competencies :
- Hands-on Experience with intelligent document processing and document indexing + document content extraction and querying, using multi modal AI Models
- Hands-on Experience with using Multi modal AI models and solutions for Imagery and Visual Creative – including text-to-image, image-to-image, image composition, image variations, etc.
- Hands-on Experience with popular AI Image Composition and Editing models from providers such as Adobe Firefly, Getty Images, ShutterStock, Flux and Flux Pro, and Stable Diffusion, and the ability to integrate them programmatically over API calls and workflows
- Hands-on Experience with Computer Vision and Image Processing using Multi-modal AI – for use cases such as object detection, automated captioning, automated masking, and image segmentation – again all done programmatically over API calls and Workflows
- Hands-on Experience with using Multi modal AI for Speech – including Text to Speech, Speech to Text, and use of Pre-built vs. Custom Voices
- Hands-on Experience with building Voice-enabled and Voice-activated experiences, using Speech AI and Voice AI solutions
- Hands-on Experience with AI Character and AI Avatar development, using a variety of different tools and platforms
- Fine-Tuning Creative AI Content models for Custom Styles, Custom Characters, and Custom Brand specific imagery
- Fine-Tuning Speech Models for Custom Voices
- Good understanding of advanced fine-tuning techniques such as LoRA
- Ability to execute and run fine-tuning workflows, end-to-end, in particular for Image Gen and Image Editing models
- Hands-on Experience with leveraging APIs to orchestrate across Multi Modal AI models
- Hands-on Experience with building workflows that orchestrate across Multi Modal AI models
- Good Experience with using AI Assistants to drive natural language interactions and orchestration with Multi Modal AI models
- Good Experience with use of AI Agents and Agentic AI workflows to drive dynamic orchestration across Multi Modal AI services and models
- Programming Skills :
- Good Expertise in
MERN stack (JavaScript)
including client-side and server-side JavaScript - Good Expertise in
Python
based development, including Python App Dev for Multi Modal AI Integration - Well-rounded in both programming languages
- Strong experience in client-side JavaScript Apps and building Static Web Apps + Dynamic Web Apps both in JavaScript
- Hands-on Experience in front-end and back-end development
- Minimum 2+ years hands-on experience in working with Full-Stack MERN apps, using both client-side and server-side JavaScript
- Minimum 2 years hands-on experience in Python development
- Minimum 2 years hands-on experience in working with LLMs and LLM models, using Python
- LLM Dev Skills :
- Solid Hands-on Experience with building end-to-end
RAG pipelines
and custom AI indexing solutions to ground LLMs and enhance LLM output - Good Experience with building
AI and LLM enabled Workflows
- Hands-on Experience
integrating LLMs with external tools such as Web Search
- Ability to leverage advanced concepts such as tool calling and function calling, with LLM models
- Hands-on Experience with
Conversational AI solutions
and chat-driven experiences Experience with multiple LLMs and models
– primarily GPT-4o, GPT o1, and o3 mini, and preferably also Gemini, Claude Sonnet, etc.- Experience and Expertise in Cloud Gen-AI platforms, services, and APIs, primarily
Azure OpenAI,
and perferably alsoAWS Bedrock
, and/or GCP Vertex AI
. - Hands-on Experience with
Assistants
and the use of Assistants
in orchestrating with LLMs - Hands-on Experience working with
AI Agents and Agent Services
.
Nice-to-Have capabilities (Not essential) :
- Hands-on Experience with building
Agentic AI workflows
that enable iterative improvement of output - Hands-on experience with both
Single-Agent
and Multi-Agent Orchestration
solutions and frameworks - Hands-on experience with different Agent communication and chaining patterns
- Ability to leverage LLMs for Reasoning and Planning workflows, that enable higher order “goals” and automated orchestration across multiple apps and tools
- Ability to leverage Graph Databases and “Knowledge Graphs” as an alternate method / replacement of Vector Databases, for enabling more relevant semantic querying and outputs via LLM models.
- Good Background with Machine Learning solutions
- Good foundational understanding of
Transformer Models
- Good foundational understanding of
Diffusion Models
- Some Experience with custom ML model development and deployment is desirable.
- Proficiency in deep learning frameworks such as PyTorch, or Keras.
- Experience with Cloud ML Platforms such as Azure ML Service, AWS Sage maker, and NVidia AI Foundry.
