Etenico Technologies
Website:
etenico.com
Job details:
Position – Data Science Lead - Architect – AI/ML
Location- Hyderabad/ Bangalore/Chennai- HYBRID
Exp- 8+
We are seeking a Principal Architect – AI/ML who will lead the design, development, and
deployment of scalable, production-grade AI/ML and GenAI solutions across Omega Healthcare’s
technology ecosystem. This is a highly technical, hands-on leadership role focused on building next-
generation AI platforms, frameworks, and intelligent systems. The role demands deep expertise in
AI/ML architecture, distributed systems, and cloud-native engineering, along with the ability to
guide teams through complex problem-solving and solution delivery.
Unlike traditional leadership roles, this position requires active involvement in architecture, coding,
model development, and system design, while mentoring engineering teams and driving technical
excellence across the organisation.
Responsibilities
AI/ML Architecture & Engineering
• Architect and develop scalable, production-ready AI/ML systems across the full lifecycle –
data ingestion, modelling, deployment, and monitoring.
• Design modular AI platforms, reusable components, and ML frameworks to accelerate
solution development.
• Lead development of high-performance ML systems leveraging distributed computing and
large-scale data processing.
Hands-on Development & Technical Leadership
• Actively contribute to coding, model development, system design, and troubleshooting.
• Provide deep technical guidance to engineering and ML teams, ensuring best practices in
design and implementation.
• Solve complex engineering challenges in model scalability, latency optimisation, and real-
time inference systems.
AI/ML & GenAI Solution Development
• Build and deploy advanced ML models, including supervised, unsupervised, and deep
learning systems.
• Drive adoption of GenAI and LLM-based solutions (RAG, embeddings, prompt engineering,
fine-tuning).
• Develop intelligent systems including document understanding & IDP, conversational AI
solutions, prediction and classification systems, and automation using NLP and AI models.
MLOps & Platform Engineering
• Establish and implement robust MLOps practices for model lifecycle management.
• Build automated pipelines for training, testing, deployment, monitoring, and retraining.
• Integrate ML workflows into CI/CD pipelines and cloud-native architectures.
Cloud & Distributed Systems
• Architect solutions across multi-cloud environments (Azure, AWS, GCP).
• Leverage containerisation, Kubernetes, microservices, and serverless architectures for AI
workloads.
• Design systems for scalability, fault tolerance, and high availability.
Data & Platform Readiness
• Work closely with data engineering teams to ensure high-quality, scalable data pipelines.
• Design feature stores, model serving layers, and data access patterns optimised for ML use
cases.
Technical Mentorship & Collaboration
• Mentor and upskill teams of ML engineers and software developers.
• Collaborate with product, engineering, and platform teams to ensure successful solution
delivery.
• Act as a technical anchor in architecture discussions, design reviews, and innovation
initiatives.
Required Education & Certifications
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related
technical field.
• Certifications in cloud platforms (AWS, Azure, GCP) or specialised AI/ML credentials are
preferred.
Work Experience
• 8+ years of experience in AI/ML, software engineering, or platform engineering roles.
• Proven experience designing and deploying AI/ML solutions in production environments.
• Strong hands-on expertise in Python, SQL, and distributed computing frameworks.
• Hands-on experience with ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience building end-to-end ML systems – not just modelling.
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI, Airflow).
• Hands-on experience with GenAI/LLMs (RAG, embeddings, fine-tuning, prompt engineering).
• Experience working with cloud platforms (AWS/Azure/GCP).
Key Skills & Competencies
Technical Skills
• Deep expertise in AI/ML architecture, distributed systems, and cloud-native engineering.
• Strong knowledge of system design, scalable architectures, data pipelines, and distributed
systems.
• Proficiency in Python, SQL, TensorFlow, PyTorch, and Scikit-learn.
• Experience with MLOps platforms and CI/CD-integrated ML workflows.
• Familiarity with vector databases, knowledge graphs, or multimodal AI systems is a plus.
• Exposure to real-time ML systems or streaming architectures is a plus.
AI & Digital Competencies
• Hands-on experience with GenAI and LLM-based solutions including RAG, embeddings, and
fine-tuning.
• Experience building AI platforms or internal ML frameworks.
• Strong understanding of AI adoption, model lifecycle management, and intelligent
automation.
Leadership & Behavioural Competencies
• Strong hands-on technical mindset with a passion for building scalable, production-grade
systems.
• Ability to operate as a player-coach – architect and active contributor simultaneously.
• Deep problem-solving skills with a focus on scalability and performance.
• Strong collaboration and stakeholder management skills across engineering, product, and
platform teams.
• Continuous learning mindset, especially in emerging AI and GenAI technologies.
Interested candidates can share there cv-
shivangi.manandhar@etenico.com
Click on Apply to know more.