Time since we first saw it
Day 38
Similar jobs usually come down between day 4 and day 77.
At Fractal, jobs usually come down by about day 45.
From 51 similar postings that came down, and 28 of Fractal’s. Coming down is not always a hire.
Lead Data Scientist
Reads like an AI Engineer role: building products on existing AI models.
Bengaluru
Live, first seen by us 38 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingWe are seeking an experienced Gen AI Solution Architect to design and deliver scalable, secure, and business-focused Generative AI solutions.
Design end-to-end Gen AI architectures using LLMs, RAG, and AI agents
Build RAG pipelines on vector databases such as Pinecone or Chroma
Architect MLOps and LLMOps pipelines for deployment and monitoring
Conduct client workshops, discovery sessions, and architecture reviews
Guide data scientists, ML engineers, and software development teams
From the employer’s posting
We are seeking an experienced Gen AI Solution Architect to design and deliver scalable, secure, and business-focused Generative AI solutions. The ideal candidate will combine deep expertise in AI/ML technologies with strong architecture, cloud, and stakeholder management skills to drive AI transformation initiatives.
Design end-to-end Generative AI architectures using LLMs, RAG, AI Agents, vector databases, and multimodal models.
Build RAG pipelines using vector databases such as Pinecone, Weaviate, Chroma, or Azure AI Search.
Architect MLOps and LLMOps pipelines for deployment, monitoring, and governance.
Conduct client workshops, discovery sessions, and architecture reviews.
Guide data scientists, ML engineers, and software development teams.
What you’ll bring
All qualificationsCore experience
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 10–15+ years of software engineering, cloud architecture, or AI experience.
- 3–5+ years of experience in AI/ML solution architecture.
Qualification wording
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
10–15+ years of software engineering, cloud architecture, or AI experience.
3–5+ years of experience in AI/ML solution architecture.
Education & alternatives
Qualifications - Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. - 10–15+ years of software engineering, cloud architecture, or AI experience.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 6, 202638 days ago
- Recorded sightings
- 52
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Fractal is hiring
28 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
- 4% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- Docker
- GCP
- Kubernetes
- Snowflake
Where the posting names them
- Machine Learning and Deep Learning - Python, SQL, REST APIs - LangChain, LangGraph, LlamaIndex, CrewAI
Cloud & Platform Architecture - Design AI solutions on AWS, Azure, or Google Cloud. - Utilize services such as Azure OpenAI, AWS Bedrock, Vertex AI, and AI Foundry.
- Design AI solutions on AWS, Azure, or Google Cloud. - Utilize services such as Azure OpenAI, AWS Bedrock, Vertex AI, and AI Foundry. - Architect MLOps and LLMOps pipelines for deployment, monitoring, and governance.
- Vector Databases (Pinecone, Weaviate, Chroma, Milvus) - AWS, Azure, GCP - Docker, Kubernetes, CI/CD
- 3–5+ years of experience in AI/ML solution architecture. - Relevant certifications preferred:- AWS Solutions Architect - Azure AI Engineer / Azure Solutions Architect
- Design prompt engineering, fine-tuning, and model optimization strategies. - Build RAG pipelines using vector databases such as Pinecone, Weaviate, Chroma, or Azure AI Search. - Implement AI agents and orchestration frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.
- Relevant certifications preferred:- AWS Solutions Architect - Azure AI Engineer / Azure Solutions Architect - Google Professional Cloud Architect
- Google Professional Cloud Architect - Databricks or Snowflake certifications If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
- AWS, Azure, GCP - Docker, Kubernetes, CI/CD - MLOps / LLMOps
Your next step
Complete your application on fractal.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
- You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
- “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
Fractal Analytics is Leading Fortune 500 companies leverage Big Data, Analytics and technology to drive smarter, faster and more accurate decisions in every aspect of their business.
Fortune 500 companies recognize analytics is a competitive advantage to understand customers and make better decisions. We deliver insight, innovation and impact to them through predictive analytics and visual story-telling.
The Artificial Intelligence and Machine Learning (AIML) group at Fractal Analytics is actively involved in helping Fortune 500 companies by enabling them to discover how they can leverage their data using advanced and sophisticated AI/ML algorithms for which we are looking for Data Scientists with the capability to work on independent statistical and machine learning research/ projects. If you are a problem solver with a curiosity for exploring new techniques and technologies in AIML space, then we would like to talk with you.
Position Summary
We are seeking an experienced Gen AI Solution Architect to design and deliver scalable, secure, and business-focused Generative AI solutions. The ideal candidate will combine deep expertise in AI/ML technologies with strong architecture, cloud, and stakeholder management skills to drive AI transformation initiatives.
Key Responsibilities
Solution Architecture & Design
- Design end-to-end Generative AI architectures using LLMs, RAG, AI Agents, vector databases, and multimodal models.
- Define scalable, secure, and cost-effective AI solution architectures.
- Create technical blueprints, architecture diagrams, and deployment strategies.
- Evaluate and recommend AI platforms, frameworks, and cloud services.
AI & LLM Engineering
- Architect solutions using models such as GPT, Claude, Gemini, Llama, Mistral, and open-source LLMs.
- Design prompt engineering, fine-tuning, and model optimization strategies.
- Build RAG pipelines using vector databases such as Pinecone, Weaviate, Chroma, or Azure AI Search.
- Implement AI agents and orchestration frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.
Cloud & Platform Architecture
- Design AI solutions on AWS, Azure, or Google Cloud.
- Utilize services such as Azure OpenAI, AWS Bedrock, Vertex AI, and AI Foundry.
- Architect MLOps and LLMOps pipelines for deployment, monitoring, and governance.
- Ensure high availability, scalability, and performance.
Business & Stakeholder Engagement
- Gather business requirements and translate them into technical solutions.
- Conduct client workshops, discovery sessions, and architecture reviews.
- Support pre-sales activities, RFP responses, solution demonstrations, and proposal creation.
- Present AI strategies and solution roadmaps to executives and stakeholders.
Governance, Security & Compliance
- Establish responsible AI practices and governance frameworks.
- Address model security, privacy, compliance, and risk management.
- Define monitoring, observability, and evaluation frameworks for AI systems.
- Ensure alignment with enterprise architecture standards.
Leadership & Mentorship
- Guide data scientists, ML engineers, and software development teams.
- Review solution designs and implementation approaches.
- Stay current with emerging Gen AI technologies and industry trends.
- Drive innovation and AI adoption across the organization.
Technical Skills
- Generative AI, LLMs, RAG, AI Agents
- Machine Learning and Deep Learning
- Python, SQL, REST APIs
- LangChain, LangGraph, LlamaIndex, CrewAI
- Vector Databases (Pinecone, Weaviate, Chroma, Milvus)
- AWS, Azure, GCP
- Docker, Kubernetes, CI/CD
- MLOps / LLMOps
- Data Architecture and Data Engineering
- AI Security and Governance
Soft Skills
- Solution design and architecture thinking
- Client-facing communication
- Stakeholder management
- Leadership and mentoring
- Problem-solving and decision-making
- Presentation and consulting skills
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 10–15+ years of software engineering, cloud architecture, or AI experience.
- 3–5+ years of experience in AI/ML solution architecture.
- Relevant certifications preferred:
- AWS Solutions Architect
- Azure AI Engineer / Azure Solutions Architect
- Google Professional Cloud Architect
- Databricks or Snowflake certifications
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!
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- Location & working pattern
Bengaluru
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