Sr. AI Engineer - Node.js / Python Coding - Bangalore
Compensation
₹3.5M–₹4.5M / yr
Location
Bengaluru
Work setup
Onsite
Seniority
Senior
Employment
Contract
Experience
2+ years
Category
Ai engineering
Posted
Skills
agentic-ai
ai
anthropic
api
aws
azure
big-data
ci-cd
cloud
cloud-native
containerization
conversational-ai
cuda
data-science
devops
docker
dspy
fine-tuning
flink
gcp
gpu
hadoop
interaction-design
kafka
kubernetes
langfuse
langgraph
langsmith
llamaindex
llm
machine-learning
neo4j
nodejs
observability
openai
pgvector
pinecone
proof-of-concept
python
pytorch
qdrant
rag
scikit-learn
spark
spring
transformers
typescript
vector-databases
weaviate
Full description
Hi We are having opening for Sr. AI Engineer -Node.js / Python Coding is mandatory. - BangaloreAbout 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
Node JS Python Coding is mandatoryPosition / DesignationSr. AI Engineer- FullStack QualificationBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related fieldYears 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 TimeOffice / Remote / Hybrid Bangalore - BellandurNumber of post1GenderMale / FemaleAnnual CTC / SalaryAs per IndustrySelection 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.
Sr. AI Engineer - Node.js / Python Coding - Bangalore at Teamplus Staffing Solution (Bengaluru) — aijobsearch
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.
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 orNode.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