Sr. Software Architect - AI

Ericsson; Dadri; Vor Ort; INR 4.000.000 - 7.000.000; Vollzeit

Zusammenfassung

Ericsson is seeking a Senior Software Architect - AI to own end-to-end architecture for GenAI solutions within the Self-Service Platform. You will design scalable, secure AI platforms leveraging LLMs, agentic frameworks, and cloud-native services.

You will guide teams on model lifecycle, MLOps standards, observability, and governance, with strong emphasis on security and Responsible AI principles.

Qualifikationen

• 15+ years in software architecture and 3+ years designing AI/ML or LLM-based systems in production.
• Deep expertise in Python (FastAPI, asyncio) and ML/DL frameworks; cloud-native services.
• Hands-on with RAG pipelines, embeddings, and vector databases for enterprise grounding.

Aufgaben

• Architect agentic AI applications using LangChain, LangGraph, and orchestration patterns.
• Design and optimize RAG solutions and integrate foundation models (Azure OpenAI, AWS Bedrock).
• Define GenAI reference architectures and evaluate LLMs, embeddings, and vector databases.
• Embed security, privacy, and Responsible AI governance from inception.

Kenntnisse

Python

LLM/GenAI

Cloud-native

Docker/Kubernetes

FastAPI

LangChain

Ausbildung

BE/B.Tech/MCA

Tools

Terraform

Redis

RabbitMQ

Arize

Jobbeschreibung

About this opportunity:

Join Ericsson as a Senior Software Architect - AI, owning end-to-end architecture for enterprise-scale GenAI and AI-powered solutions within our Self-Service Platform (SSP). You will design scalable, secure, production-grade AI platforms leveraging agentic frameworks, LLMs, and cloud-native services. You will establish reference architectures across RAG, memory, evaluation, and observability while guiding teams across the full model lifecycle - at the intersection of AI innovation and Responsible AI governance.

What you will do:

• Architect agentic AI applications using LangChain, LangGraph, and orchestration patterns; define prompt strategies, guardrails, and structured outputs aligned to product and risk requirements.
• Design and optimize RAG solutions (chunking, embeddings, retrieval, re-ranking) and own foundation model integrations (Azure OpenAI, AWS Bedrock, on-prem LLMs) with routing, fallbacks, and cost/performance optimization.
• Define GenAI reference architectures; evaluate and select LLMs, embedding models, vector databases, and orchestration frameworks based on performance, compliance, and cost.
• Embed security, privacy, and Responsible AI governance from inception - covering PII handling, data access controls, and content guardrails.
• Build scalable backend APIs using Python (FastAPI, asyncio) with REST/JSON-RPC interfaces and resilience patterns (Redis, RabbitMQ); guide teams on MLOps/LLMOps standards including deployment, monitoring, retraining, and drift handling.
• Define LLM evaluation strategies, implement observability/tracing (Arize, LangSmith), and design memory strategies with retention and replay safety for long-running assistants.
• Containerize and deploy services via Docker and Kubernetes; govern CI/CD pipelines with automated testing, security scanning, and IaC (Terraform or equivalent).

The skills you bring:

• BE/B.Tech/MCA in Computer Science, Engineering, or equivalent, with 15+ years in software architecture and relevant 3+ years designing AI/ML or LLM-based systems in production.
• All academic credentials must be from recognized and accredited institutions and are further subject to verification.
• Deep expertise in Python (FastAPI, asyncio) and ML/DL frameworks (PyTorch, TensorFlow); strong experience with distributed, cloud-native services.
• Hands-on with RAG pipelines, embeddings, and vector databases (Elastic, Pinecone, Milvus, Chroma) for enterprise knowledge grounding.
• Hands on Python experience mandatory
• Proven experience with agentic GenAI frameworks (LangChain, LangGraph, LlamaIndex, AutoGen) and interoperability patterns such as Model Context Protocol (MCP).
• Strong knowledge of LLM architectures, fine-tuning techniques (LoRA, PEFT), and experience with Azure OpenAI and/or AWS Bedrock.
• Solid understanding of MLOps/LLMOps, Responsible AI principles, and embedding governance into GenAI design. Proficiency with Docker, Kubernetes, Terraform, and CI/CD for cloud-native AI deployments.
• Good to Have: LLM observability tools (Arize, LangSmith), Azure enterprise services (AKS, Key Vault), memory frameworks (MemGPT, LangMem), knowledge graph experience, and Telecom industry AI adoption background.
• Locations: Bangalore, Kolkata, Gurgaon, Noida, Chennai

Why join Ericsson?

At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

What happens once you apply?

Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do.

We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth.

We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team.

Ericsson is proud to be an Equal Opportunity Employer.

Primary country and city:

India (IN) || Noida