CENTOTECH SERVICES PRIVATE LIMITED
Website:
centotech.com
Job details:
Company Description
CentoTech Services Private Limited is a global leader in ERP and custom software solutions, with a strong focus on addressing cutting-edge technological challenges. Operating as a Digital IT Consulting and Services partner, CentoTech collaborates with top organizations across the globe, with offices in India, the USA, and the UK. Leveraging a deep understanding of industries and exceptional geographical reach, CentoTech delivers innovative solutions to complex challenges. We are committed to driving impact in today’s ever-evolving digital landscape with expertise, scale, and a passion for innovation.
Role Description
Design and implement LLM-powered applications including RAG pipelines, AI agents,
chatbots, and generative AI integrations
• Build and optimize ML/data science pipelines for training, fine-tuning, and evaluating
models
• Architect and maintain AI infrastructure: containerized deployments, CI/CD for ML, model
monitoring, and scaling
• Integrate with commercial LLM APIs (OpenAI, Anthropic, etc.) and open-source models
• Meet with business users and stakeholders to interpret requirements, scope AI use cases,
and translate ambiguous needs into clear technical specifications
• Collaborate with product, engineering, and non-technical teams to align AI solutions with
business objectives and user workflows
• Establish best practices for prompt engineering, model evaluation, and responsible AI
development
• Document architectures,
Qualifications
7+ years of exp is mandatory
Proven track record designing and shipping enterprise AI/ML systems in production
• Deep expertise in Python, PyTorch/TensorFlow, and modern ML frameworks
• Experience with cloud-native AI services on AWS, GCP, or Azure
• Strong background in Kubernetes, Docker, and container orchestration for ML workloads
• Ability to lead technical architecture decisions and mentor junior team members
• Strong communication skills with a proven ability to engage business stakeholders, run
discovery sessions, and distill requirements into actionable plans
• Experience with LLM application patterns: retrieval-augmented generation, function
- calling, embeddings, vector databases
Nice to Have
• Experience with MLOps platforms (MLflow, Weights & Biases, SageMaker, Vertex AI)
• Background in computer vision, NLP, or time-series forecasting
• Contributions to open-source AI/ML projects
• Experience building multi-agent systems or complex AI orchestration workflows
• Familiarity with geospatial data, satellite imagery, or remote sensing
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