UST
Website:
ust.com
Job details:
Role Description
Job Title: Senior AI Engineer
Experience: 7–10 Years
Job Summary
UST is seeking a highly experienced Senior AI Engineer to design, develop, and deploy enterprise‑grade Generative/Agentic AI solutions. The role requires strong hands‑on engineering expertise, the ability to translate complex business requirements into scalable AI systems, and experience delivering production‑ready solutions in collaboration with cross‑functional teams.
This position plays a critical role in driving AI innovation, ensuring operational excellence, and supporting data‑driven decision‑making across enterprise platforms.
Key Responsibilities
- Design, develop, test, and optimize Agentic and Generative AI solutions aligned with business and enterprise architecture standards
- Translate business requirements into analytical and AI solution designs, workflows, and technical specifications
- Implement LLM‑based solutions, including prompt engineering, RAG pipelines, and model optimization.
- Collaborate effectively with business stakeholders, product owners, UX teams, data engineers, and platform teams
- Drive technical discussions, solution roadmap alignment, and architecture reviews
- Ensure adherence to data confidentiality, security, and compliance standards
- Prepare and maintain comprehensive documentation, including technical designs, workflows, and user guides
- Monitor project progress, resolve technical issues, and provide regular status reporting to stakeholders
- Continuously improve AI systems by evaluating current practices and recommending enhancements.
- Build, train, evaluate, and deploy machine learning and deep learning models at enterprise scale
Must‑Have Requirements
- Technical Competencies
- 7–10 years of overall IT experience with 4+ years of hands‑on experience in AI engineering
- Experience with Cloud platforms: AWS or Azure
- Demonstrated experience building production-grade Applied Agentic or GenAI solutions.
- Strong programming experience in Python & SQL and frameworks like LangChain, LangGraph, CrewAI, Claude Code, Cursor etc and solid software engineering fundamentals.
- Knowledge of monitoring, logging, and performance optimization for AI workloads
- Experience with Generative/Agentic AI and Large Language Models (LLMs):
- Prompt engineering
- Retrieval‑Augmented Generation (RAG)
- Model evaluation (Hallucination rate, Grounded vs ungrounded responses, Prompt robustness)
- Hyperparameter tuning (Chunk size and overlap, Embedding, Retrieval top‑k/top-p)
- Strong experience in end‑to‑end AI solution lifecycle, including:
- Model development and deployment
- Performance monitoring and optimization
Behavioral Competencies
- Strong analytical, critical thinking, and problem‑solving skills
- Strong ownership mindset with accountability for delivery and quality
- Ability to clearly articulate complex technical concepts to non‑technical stakeholders
- Demonstrated experience working with cross‑functional and geographically distributed teams
- Excellent written and verbal communication skills
- Ability to work effectively in structured, enterprise‑governed environments
Good‑to‑Have Requirements
- Technical Competencies
- Understanding of data engineering concepts such as ETL/ELT, data pipelines, batch and streaming basics, data modelling, and handling structured / unstructured data.
- Hands‑on experience with ML/DL frameworks:
- TensorFlow
- PyTorch
- Scikit‑learn
- Experience with Big Data technologies:
- Apache Spark
- Databricks
- Kafka
- Knowledge and hands‑on experience with Machine Learning, including:
- Time series analysis
- Neural Networks
- Support Vector Machines (SVM)
Skills
agentic ai,generative ai,llmops,python,
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