Senior Solution Architect – AI Data & LLM Solutions
- Location
- Pan India
- Salary
- Not specified
- Company
- Akash pawar
Job description
• Role & Company / Project Overview: We are looking for a Senior Solution Architect with strong expertise in AI/ML, LLM solutions, and data engineering to lead complex, client-facing AI engagements. The ideal candidate should be comfortable working directly with CTOs, VPs of Engineering, and AI research leaders while designing and building scalable AI data-generation, labeling, and evaluation pipelines. • Key Responsibilities & Daily Duties: - Lead technical discussions with CTOs, VPs, and senior AI/ML stakeholders. - Identify client requirements and translate business or research goals into effective AI data strategies. - Design and build AI-driven solutions and automated, multi-stage data pipelines. - Develop data-labeling components, quality controls, and evaluation workflows. - Conduct experiments to validate data quality, performance, and scalability. - Drive solutions from MVP to production. - Establish engineering standards and mentor Solution Engineers and Technical Consultants. - Own end-to-end delivery, technical quality, timelines, scalability, and commercial outcomes. - Identify opportunities to expand client engagements. • Required Qualifications, Skills & Experience: - Experience: 7–10 Years. - Priority: Hands-on LLM Post-Training Experience. - Strong understanding of LLM training, fine-tuning, and evaluation. - Hands-on knowledge of SFT (Supervised Fine-Tuning) and Reinforcement Learning. - Knowledge of RLHF/RLAIF, DPO/PPO, reward modeling, and LoRA/PEFT. - AI solution architecture and multi-stage pipeline development. - Agentic AI workflows, RAG, and synthetic data generation. - Proficiency in Python, NumPy, Pandas, and API integration. - LLM-powered solution prototyping. - Data labeling, quality controls, and AI evaluation strategies. - Software engineering fundamentals, testing, version control, and iterative development. - Important Requirement: Candidates must have a strong understanding of LLM post-training, particularly SFT and Reinforcement Learning, along with excellent executive communication skills and hands-on solution engineering experience. - Preferred: Experience building production-grade AI/ML solutions, proven technical leadership and mentoring experience, background in applied ML/LLM engineering or top-tier strategy consulting, hands-on LLM fine-tuning and agentic AI development, MSc/PhD in AI, Computer Science, or a related field, and experience with data-centric AI, crowdsourcing, or frontier AI projects. • Working Hours, Shifts & Location Details: - Location: Remote. - Shift: US / Europe Time Zones. • Application Instructions: Interested candidates, please share your updated resume and LinkedIn profile via the provided contact channels.