Clock Edge Technologies Pvt Lt→
AI/ML Computational Science Specialist at Clock Edge… · Bangalore…
Job Description
AI/ML Computational Science Specialist
Experience: 5–8 Years
Designation: AI/ML Computational Science Specialist
Skill Required: Artificial Intelligence (AI)
Qualification: BTech / BE / BCA
Language: English (International) – Intermediate
Role Overview
The RDE-AI/ML Computational Science Specialist will design, build, integrate, test, and deploy AI-native and Agentic AI solutions.
The role requires strong Python and AI/ML capability, supported by working knowledge across integration, cloud, DevOps, testing, observability, responsible AI, and enterprise platforms.
Key Responsibilities
Own design and build of complex Python-led AI/ML and Agentic AI modules across the delivery lifecycle.
Design and implement agent workflows, tool-calling patterns, RAG pipelines, vector search, and enterprise grounding approaches.
Guide junior engineers through code reviews, design clarifications, testing practices, and technical issue resolution.
Drive API, microservices, and enterprise platform integration readiness.
Contribute to AI testing, observability, responsible AI controls, monitoring, performance optimization, and production support.
Must-Have Skills
Python & Full-Stack Development
Strong Python engineering
Async programming
OOP
Data structures
Scripting
Production AI pipeline development
Agentic AI
LangChain
LangGraph
MCP
RAG
Agent orchestration
Tool use
Function calling
Memory/state management
Workflow design
GenAI / LLM
GenAI and LLMs
Prompt engineering
Structured outputs
RAG
Vector databases
Semantic search
Integration & Engineering
REST APIs
Microservices
Enterprise integration
Testing
Debugging
Secondary Skills
LangGraph, LangChain, Semantic Kernel, CrewAI or equivalent
Azure / AWS / GCP
Docker
Kubernetes
CI/CD
GitOps
Deployment automation
Responsible AI
LLMOps
AI evaluation
Monitoring
OAuth
Azure AD
Enterprise security practices
Additional Technical Areas
AI agent design and reasoning loops
Orchestration and multi-agent coordination
Tool calling and function routing
Agent memory and state management
LLMs such as GPT, Claude, Gemini
Few-shot and structured output techniques
Vector databases such as Pinecone, Weaviate, and ChromaDB
REST/GraphQL API development
Cloud-native architecture
Managed AI services
Docker/Kubernetes
CI/CD and automated deployment
AI guardrails and enterprise compliance
LLM output evaluation
Observability and tracing
Performance tuning and cost optimization
Enterprise integration with platforms such as ServiceNow, Appian, SAP, Salesforce, and Microsoft ecosystem
Pay: Up to ₹1,800,000.00 per year
Work Location: In person