Lumen Technologies
Website:
lumen.com
Job details:
About Lumen Technologies
Lumen Technologies is a global technology company that delivers innovative communication and network solutions. Our mission is to empower businesses and individuals to connect, grow, and thrive in the digital age. With a focus on customer experience and operational excellence, we strive to provide cutting-edge solutions that meet the evolving needs of our customers.
Job Details: 13711
Location: Bengaluru
Work Mode: Hybrid (WFO – 1 day per week OR 4 days per month)
Mandatory Skills
Machine Learning, Artificial Intelligence, Natural Language Processing, Python, SQL, Generative AI, Agentic AI, ML
Mandatory Technical Keywords
Machine Learning, Artificial Intelligence, Generative AI, Agentic AI, Large Language Models, RAG, Python, SQL, NLP, ML Architecture
Job Description
Department: Data Science / AI Center of Excellence
Experience: 12–15+ years
Job Summary
- As a Lead Solutions AI Architect, you will play a technical and strategic leadership role in driving enterprise‑scale analytics, Generative AI, and Agentic AI initiatives across business units and industries.
- You will own solution architecture, influence AI strategy, mentor senior data scientists, and partner with leadership to translate business priorities into scalable AI solutions.
- This role requires deep hands‑on expertise, strong architectural judgment, and the ability to operate as a trusted advisor to clients and internal stakeholders.
- You are expected to set technical standards, evaluate emerging GenAI technologies, and ensure responsible, scalable adoption of AI across the organization.
Key Responsibilities
- Lead the design and delivery of complex AI/GenAI solutions from problem framing through production deployment
- Own end‑to‑end solution architecture for LLM‑powered, RAG‑based, and Agentic AI systems
- Act as a technical authority and advisor for clients and senior stakeholders on AI strategy and feasibility
- Drive best practices, standards, and governance for ML and GenAI development
- Mentor and review work of senior data scientists and consultants, raising overall team capability
- Collaborate with product, engineering, security, and compliance teams to ensure scalable and responsible AI adoption
- Evaluate and recommend emerging tools, frameworks, and architectures in the GenAI ecosystem
Mandatory Skills
- Core Data Science & ML Expert‑level proficiency in Python and SQL for analytics, modeling, and solution development
- Strong command of machine learning techniques, including regression, classification, clustering, model evaluation, and trade‑off analysis
- Advanced experience in data wrangling, feature engineering, and transformation using Pandas, NumPy, and related libraries
- Ability to design insight‑driven visualizations and executive dashboards using Power BI or Tableau
- Deep understanding of statistical analysis, hypothesis testing, experimentation, and model interpretability
Cloud & Production AI
Proven experience architecting and deploying AI solutions on AWS, Azure, or GCP
Strong understanding of scalable data workflows, APIs, and cloud‑native architectures
Ability to balance performance, cost, security, and maintainability in production systems
Generative AI & Agentic AI (Advanced) - Hands‑on leadership experience with Generative AI and Large Language Models, including:
- Advanced prompt engineering and orchestration strategies
- Fine‑tuning, deployment, and lifecycle management using OpenAI, Azure OpenAI, Hugging Face APIs
- Strong understanding of AI ethics, governance, and responsible GenAI design
- Deep expertise in GenAI architectures and frameworks, including:
- LangChain for complex LLM‑powered workflows
- LangGraph for designing and managing Agentic AI systems
- Advanced RAG architectures (Hierarchical RAG, Multimodal RAG, Agentic RAG)
- Vector databases such as FAISS, Pinecone, or Azure AI Search
- Multimodal AI solutions combining text, image, and/or audio inputs
- Ability to make architectural decisions around memory, tool use, agent coordination, and evaluation in multi‑agent systems
Communication & Leadership
- Excellent executive‑level communication skills—able to explain complex AI concepts to non‑technical audiences
- Strong documentation, presentation, and client‑engagement skills Proven ability to influence without authority and drive alignment across teams
Nice‑to‑Have Skills - Strong experience with big‑data platforms such as Apache Spark, Hadoop, or Databricks Advanced MLOps and LLMOps experience, including CI/CD, monitoring, observability, and model governance
- Domain leadership in industries such as BFSI, Healthcare, Retail, or Telecom
- Hands‑on exposure to advanced AI specializations:
- Natural Language Processing (spaCy, NLTK)
- Computer Vision (OpenCV, YOLO)
- Relevant senior‑level certifications in Cloud, AI, or Machine Learning (AWS, Azure, or equivalent)
"We are an equal opportunity employer committed to fair and ethical hiring practices. We do not charge any fees or accept any form of payment from candidates at any stage of the recruitment process. If anyone claims to offer employment opportunities in our company in exchange for money or any other benefit, please treat it as fraudulent and report it immediately."
Machine Learning, Artificial Intelligence, Natural Language Processing, Python, SQL, Generative AI, Agentic AI, ML
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