Up Java senior engineer Jobs – 139 Open Jobs Today

Group Technical Architect
HCLTech —Greater Noida, Uttar Pradesh
- Azure
- System design
- Java
10d
Senior Lead - AI/ML
Nucleus Software —Noida, Uttar Pradesh
- Java
- Bachelor's degree
- Machine learning
Android App Developer
INSTAACODERS TECHNOLOGIES —Noida, Uttar Pradesh
- Remote
- Java
- Bachelor's degree
- APIs
- Work from home
Senior Site Reliability Engineer I
Sumo Logic —Noida, Uttar Pradesh
- Computer Science
- Java
- Master's degree
SDET - Senior Engineer
Iris Software —Noida, Uttar Pradesh
- Software troubleshooting
- Java
- SQL
- Health insurance
1h
SDET - Senior Engineer
Iris Software —Noida, Uttar Pradesh
- Software troubleshooting
- Java
- APIs
- Health insurance
1h

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\*Ensure compliance with technical specifications, engineering drawing, and industry standards. Salary Range*- 70-75k CTC pm (Salary is negotiable based on…
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This is a hands-on role with significant influence over our infrastructure strategy, deployment workflows, and engineering culture.
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Group Technical Architect

HCLTech -
Greater Noida, Uttar Pradesh

Apply Now

Job details

10 days ago

Qualifications

CI/CD
Azure
Law
Kubernetes
System design
Java
Master's degree
AWS
Docker
Continuous integration
AI
Python

Full job description

| Greater Noida, Uttar PradeshBengaluru, Karnataka
Job Summary
Role Summary

The AI Technical / Engineering Manager is a senior, hands-on leadership role responsible for delivering complex AI and Generative AI programs from architecture through production at enterprise scale. This role combines deep technical expertise in AI systems with delivery leadership, ensuring that AI solutions are engineered correctly, operate reliably, and deliver measurable business outcomes. Unlike traditional delivery managers, this role remains technically accountable for AI design quality, non-functional requirements, and production readiness.

Core Responsibilities

Own end-to-end delivery of AI and GenAI programs, from solution design to production rollout and steady-state operations.
Provide technical leadership across AI Engineers, Fullstack Engineers, LLMOps, Observability, QA, and RAI roles.
Ensure AI system architectures meet scalability, reliability, security, observability, and cost targets.
Actively participate in architectural decisions for RAG pipelines, agent-based systems, model selection, and data strategies.
Drive engineering excellence through code reviews, design reviews, and technical governance forums.
Establish delivery plans, sprint structures, and release strategies tailored for AI systems.
Track technical KPIs including AI quality metrics, latency, cost, availability, and incident rates.
Lead incident triaging, RCA, and continuous improvement for AI production systems.
Ensure Responsible AI, security, and compliance controls are embedded into delivery workflows.

Key Responsibilities
AI System Engineering Expertise

Deep understanding of AI and Generative AI system design, including LLMs, embeddings, vector search, and retrieval pipelines.
Strong experience with Retrieval-Augmented Generation (RAG) architectures and grounding strategies.
Knowledge of agentic AI patterns including planners, tool/function calling, memory, and workflow orchestration.
Experience operating distributed AI systems with strict latency, cost, and reliability requirements.
Practical understanding of AI observability, drift detection, and quality evaluation techniques.
Familiarity with Responsible AI risks, guardrails, human-in-the-loop patterns, and safety controls.

Tools & Technology Stack

Programming languages: Python (mandatory), Java or equivalent backend languages.
LLM platforms: Azure OpenAI, OpenAI, Anthropic, Google Vertex AI, or equivalent.
AI frameworks: LangChain, LlamaIndex, LangGraph, or similar orchestration frameworks.
Vector databases: Pinecone, FAISS, Weaviate, Azure AI Search.
Cloud platforms: Azure (preferred), AWS, GCP.
Platform & Ops: Docker, Kubernetes, CI/CD pipelines, infrastructure-as-code.
Observability: OpenTelemetry concepts, dashboards, AI-specific telemetry.

Leadership & Delivery Accountability

The AI Technical / Engineering Manager is accountable for engineering outcomes, not just project milestones. This role ensures teams build the right AI solutions correctly, scale them safely, and operate them reliably.

Skill Requirements
Experience & Qualifications

10–15 years of experience in software engineering, architecture, or platform roles, with leadership responsibility.
4–6+ years delivering AI / ML / Generative AI systems in production environments.
Proven experience leading multi-disciplinary engineering teams delivering enterprise-scale AI solutions.

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Group Technical Architect

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Android App Developer

Senior Site Reliability Engineer I

SDET - Senior Engineer

SDET - Senior Engineer

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