Sr. AI Engineer - Node.js / Python Coding - Bangalore

Teamplus Staffing Solution

Bengaluru

Presencial

INR 4.000.000 - 6.000.000

Jornada completa

Hace 4 días
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Descripción de la vacante

Teamplus Staffing Solution in Bangalore is seeking a Sr. AI Engineer (Full-Stack) with Node.js and Python coding mandatories to design, build, and productionize AI-powered agents.

You will work with product, research, and engineering teams to translate requirements into end-to-end AI solutions, including RAG, multi-agent orchestration, and scalable backend services. This role emphasizes production readiness, observability, and responsible AI practices, with a focus on delivering reliable systems

Formación

  • 8+ years in software or AI/ML with production-grade apps.
  • 4+ years building AI-centric systems.
  • 2+ years with LLM-based agents and multi-agent orchestration.
  • Solid Python and full-stack skills.

Responsabilidades

  • Design and build Stateful, multi-agent AI systems for scalable workflows.
  • Collaborate with Product, Research and stakeholders to deliver end-to-end AI solutions.
  • Implement RAG with hybrid search and advanced retrieval techniques.
  • Develop scalable backend services and lightweight frontend tools.
  • Optimize batching, streaming, caching, and orchestration in async environments.
  • Improve latency, throughput, observability and reliability.
  • Work with GPU-enabled cloud environments.
  • Establish monitoring, tracing, observability for AI systems.
  • Develop reusable MCPs / APIs and best practices.
  • Drive evaluation-driven adoption of AI technologies.
  • Stay current with AI advancements and apply them.
  • Ensure responsible AI, privacy and security standards.

Conocimientos

Python
Node.js
Full-stack
LLM
AI systems
Observability
Cloud

Herramientas

LangGraph
LlamaIndex Workflows
LangSmith
LangFuse
Arize Phoenix
PyTorch
Transformers

Descripción del empleo

Hi

We are having opening for Sr. AI Engineer - Node.js / Python Coding is mandatory. - Bangalore

About the Team:

As an AI Engineer focused on Production AI Agents, you will partner closely with Product, Research, Engineering, and cross-functional stakeholders to design, build, and scale AI- powered systems that enhance how insights are generated and operationalized. This role emphasizes moving beyond experimentation to deliver reliable, evaluation-driven AI solutions that integrate seamlessly into real workflows. You will play a key role in shaping AI ecosystem by building robust agent architectures, ensuring production readiness, and continuously improving system performance and trust.

Working Days:

Monday Friday

Job Timing:

Dayshift

Position / Designation

Sr. AI Engineer- FullStack Qualification

Years of Experience
  • 8+ years of experience in software engineering, AI/ML engineering, or full-stack development, with hands-on ownership of building and deploying production-grade applications or platforms.
  • 4+ years of focused experience building and deploying AI-centric systems.
  • 2+ years of hands-on experience with LLM-based agents, autonomous workflows, or multi-agent orchestration.
Permanent / Contract (If contract, period ?)

Permanent Full Time

Office / Remote / Hybrid

Bangalore - Bellandur

Number of post

1

Gender

Male / Female

Annual CTC / Salary

As per Industry

Selection Process

1- Total 3 Technical round
2- 2 rounds evaluation with LV (we can plan to take this together based on panel availability) & 1 with client

Job Role & Responsibility
  • Design and build stateful, multi-agent AI systems using modern orchestration frameworks, enabling scalable and reliable workflows for insights generation and synthesis.
  • Collaborate with Product, Research, and business stakeholders to translate requirements into end-to-end AI solutions, from proof of concept through evaluation and production deployment.
  • Solid understanding of Retrieval-Augmented Generation (RAG), including hybrid search, re-ranking, and advanced retrieval techniques.
  • Implement evaluation frameworks and pipelines (e.g., LLM-as-a-Judge, automated benchmarks) to measure system performance, reliability, and quality before and after release.
  • Develop and maintain scalable backend services for high-throughput, low-latency workloads, while contributing to lightweight frontend components to deliver functional prototypes and internal tools.
  • Optimize batching, streaming, caching, and request orchestration in distributed and async environments.
  • Improve production systems across latency, throughput, reliability, observability, and unit economics.
  • Partner with infrastructure teams to leverage GPU-enabled and cloud-native environments effectively.
  • Establish monitoring, tracing, and observability practices for complex AI systems, ensuring performance, reliability, and debuggability in production.
  • Develop reusable platform components, MCPs / APIs, and best practices for AI application development.
  • Drive a pragmatic, evaluation-driven approach to adopting new AI technologies, balancing innovation with reliability and business impact.
  • Stay current with advancements in AI (e.g., reasoning models, SLMs, prompting strategies) and apply them to improve systems and workflows.
  • Partner with cross-functional teams to ensure AI solutions align with responsible AI, privacy, and security standards.
Skills
  • Skills48 years of experience in software engineering, AI/ML engineering, or full-stack development, with hands-on ownership of building and deploying production-grade applications or platforms.
  • 4+ years of focused experience building and deploying AI-centric systems.
  • 2+ years of hands-on experience with LLM-based agents, autonomous workflows, or multi-agent orchestration.
  • Strong full-stack engineering experience, with deep expertise in Python and familiarity with TypeScript or Node.js.
  • Hands-on experience with AI orchestration frameworks such as LangGraph, LlamaIndex Workflows, or similar tools.
  • Solid understanding of Retrieval-Augmented Generation (RAG), including hybrid search, re-ranking, and advanced retrieval techniques.
  • Experience implementing observability and tracing for AI systems (e.g., LangSmith, LangFuse, Arize Phoenix).
  • Production experience with modern ML tooling and frameworks (for example: PyTorch, Transformers, scikit-learn).
  • Proven experience taking AI-powered products from prototype to production with strong maintainability and operational quality.
  • Proven ability to design and execute evaluation pipelines and testing frameworks to ensure reliability and reduce hallucinations.
  • Experience working with APIs/SDKs from major model providers (OpenAI, Anthropic, Gemini) and open-source models.
  • Experience deploying and managing services on cloud platforms (AWS, Azure, or GCP) and using containerization (Docker/Kubernetes).
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Strong collaboration and communication skills, with the ability to work effectively across technical and non-technical teams. Experience with Spring-based service development.
  • Familiarity with big data and processing ecosystems (for example: Spark, Hadoop).
  • Experience with streaming systems (for example: Kafka, Flink, Beam).
  • Experience with RAG pipelines, vector stores, tool-use frameworks, and multimodal model integration.
  • Exposure to GPU optimization and performance tuning (for example: CUDA, inference optimization techniques).
  • Experience building conversational AI systems (intents, entities, dialog flows, and interaction design).
  • Familiarity with prompt optimization tools such as DSPy.
  • Proficiency with vector databases (Pinecone, Weaviate, Qdrant, pgvector).
  • Exposure to voice agents or multimodal AI systems.
  • Experience with graph databases (e.g., Neo4j) or GraphRAG approaches.
  • Foundational knowledge of machine learning or model fine-tuning.
  • Joining DateNeed Immediate to 15 days
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