Senior Solution Architect
HCLTech
Date: 2 weeks ago
City: Hyderabad, Telangana
Contract type: Full time
Hyderabad, Telangana
Job Summary
We are seeking an experienced Senior Solution Director, who will play a pivotal role in architecting , leading , and actively contributing to the development of AI, GenAI and Analytics applications, machine learning models , and cloud-native infrastructure . This hands-on leadership position requires extensive technical expertise and experience in managing a diverse, cross-functional team of engineers spanning GenAI App Development, Data Science , Machine Learning , Full Stack , DevOps , Cloud Infrastructure , and API development .
You will be responsible for shaping new opportunities, architecting complex systems , making critical decisions, and leading teams to deliver high-quality, scalable solutions while remaining directly involved in coding , technical design , and problem-solving .
Key Responsibilities
null
Skill Requirements
Skill Matrix - Gen AI/AIML (E5 Band)
Years of Exp - E 5: TEX: 14+yrs; REX: 10+yrs
Location - Noida, Bangalore, Hyd, Chennai.
Project type (Support / Dev / Maintenance / Testing) - Dev
Team Handling / Individual Contributor - Both
Notice Period - P1:0-30days; P2: 30-45days: P3: 45-90days
Skill | Mandatory | Proficiency Level (1-5)
Python | Yes | 5
ML Model Development | Yes | 5
Kafka,Spark, PostgreSQL | Yes | 5
scikit-learn, PyTorch, pandas, NumPy, XGBoost, Spark, Apache Spark,Apache Airflow,Apache Kafka, RabbitMQ,PostgreSQL, MySQL | Yes | 5
R, Bash, TensorFlow, XGBoost, LightGBM, Mllib,Classical ML, Deep Learning, NLP, Time Series Forecasting, DataBricks | Nice to have | 4
Other Requirements
Key Responsibilities: Hands-on Technical Leadership & Oversight: • Architecting Scalable Systems: Lead the design of AI, GenAI solutions, machine learning pipelines, and data architectures that ensure performance, scalability, and resilience. • Hands-on Development: Actively contribute to coding, code reviews, solution design, and hands-on troubleshooting for critical components of GenAI, ML, and data pipelines. • Cross-Functional Collaboration: Work with Account Teams, Client Partners and Domain SMEs to ensure alignment between technical solutions and business needs. • Team Leadership: Mentor and guide engineers across various functions including AI, GenAI, Full Stack, Data Pipelines, DevOps, and Machine Learning, fostering a collaborative and high-performance team environment. Solution Design & Architecture: • System & API Architecture: Design and implement microservices architectures, RESTful APIs, cloud-based services, and machine learning models that integrate seamlessly into GenAI and data platforms. • AI, GenAI, Agentic AI Integration: Lead the integration of AI, GenAI, and Agentic applications, NLP models, and large language models(e.g., GPT, BERT) into scalable production systems. • Data Pipelines: Architect ETL pipelines, data lakes, and data warehouses using industry-leading tools like Apache Spark, Airflow, and Google BigQuery. • Cloud Infrastructure: Drive the deployment and scaling of solutions using cloud platforms like AWS, Azure, GCP, and other relevant cloud-native technologies. Machine Learning & AI Solutions: • ML Integration: Lead the design and deployment of machine learning m
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Job Summary
We are seeking an experienced Senior Solution Director, who will play a pivotal role in architecting , leading , and actively contributing to the development of AI, GenAI and Analytics applications, machine learning models , and cloud-native infrastructure . This hands-on leadership position requires extensive technical expertise and experience in managing a diverse, cross-functional team of engineers spanning GenAI App Development, Data Science , Machine Learning , Full Stack , DevOps , Cloud Infrastructure , and API development .
You will be responsible for shaping new opportunities, architecting complex systems , making critical decisions, and leading teams to deliver high-quality, scalable solutions while remaining directly involved in coding , technical design , and problem-solving .
Key Responsibilities
null
Skill Requirements
Skill Matrix - Gen AI/AIML (E5 Band)
Years of Exp - E 5: TEX: 14+yrs; REX: 10+yrs
Location - Noida, Bangalore, Hyd, Chennai.
Project type (Support / Dev / Maintenance / Testing) - Dev
Team Handling / Individual Contributor - Both
Notice Period - P1:0-30days; P2: 30-45days: P3: 45-90days
Skill | Mandatory | Proficiency Level (1-5)
Python | Yes | 5
ML Model Development | Yes | 5
Kafka,Spark, PostgreSQL | Yes | 5
scikit-learn, PyTorch, pandas, NumPy, XGBoost, Spark, Apache Spark,Apache Airflow,Apache Kafka, RabbitMQ,PostgreSQL, MySQL | Yes | 5
R, Bash, TensorFlow, XGBoost, LightGBM, Mllib,Classical ML, Deep Learning, NLP, Time Series Forecasting, DataBricks | Nice to have | 4
Other Requirements
Key Responsibilities: Hands-on Technical Leadership & Oversight: • Architecting Scalable Systems: Lead the design of AI, GenAI solutions, machine learning pipelines, and data architectures that ensure performance, scalability, and resilience. • Hands-on Development: Actively contribute to coding, code reviews, solution design, and hands-on troubleshooting for critical components of GenAI, ML, and data pipelines. • Cross-Functional Collaboration: Work with Account Teams, Client Partners and Domain SMEs to ensure alignment between technical solutions and business needs. • Team Leadership: Mentor and guide engineers across various functions including AI, GenAI, Full Stack, Data Pipelines, DevOps, and Machine Learning, fostering a collaborative and high-performance team environment. Solution Design & Architecture: • System & API Architecture: Design and implement microservices architectures, RESTful APIs, cloud-based services, and machine learning models that integrate seamlessly into GenAI and data platforms. • AI, GenAI, Agentic AI Integration: Lead the integration of AI, GenAI, and Agentic applications, NLP models, and large language models(e.g., GPT, BERT) into scalable production systems. • Data Pipelines: Architect ETL pipelines, data lakes, and data warehouses using industry-leading tools like Apache Spark, Airflow, and Google BigQuery. • Cloud Infrastructure: Drive the deployment and scaling of solutions using cloud platforms like AWS, Azure, GCP, and other relevant cloud-native technologies. Machine Learning & AI Solutions: • ML Integration: Lead the design and deployment of machine learning m
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