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Full Stack AI Engineer (AI / Python coding / Nodejs) - Bangalore

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Onsite

Full Stack AI Engineer (AI / Python coding / Nodejs) - Bangalore

Teamplus Staffing Solution

Full Stack AI Engineer (AI / Python coding / Nodejs) - Bangalore

Skills

Google Cloud PlatformBig DataDockerNodeTypescriptPythonData SciencePyTorchSpring BootKafkaNeo4jMachine LearningAIAWSKubernetesHadoopAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹3,000,000 – ₹3,500,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

19 August 2026

What they need


Hi,
We are having opening for Full Stack AI Engineer - (AI / Python coding / Nodejs) - Bangalore

Working Days: Monday Friday
Job Timing: 9AM 6PM

Position / DesignationFull stack DeveloperQualificationBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related fieldYears of Experience

  • 5+ 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 TimeOffice / Remote / Hybrid Bangalore - Bellandur Number of post1GenderMale / FemaleAnnual CTC / SalaryUpto 35 LPASelection Process1- 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

  • 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.

Preferred Qualifications:

  • 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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