Senior Automation Engineer

Ericsson; Dadri; Sur place; INR 3 500 000 - 7 000 000; Plein temps

Résumé du poste

Ericsson in Noida, India seeks an AI/ML Solution Architect to design end-to-end technical blueprints for secure, scalable AI/ML systems. You will bridge business goals with engineering execution and lead cross-functional teams in system design and governance.

The role emphasizes RAG architectures, real-time inference, and platform choices across AWS, Azure, or GCP. Strong leadership and telecom domain knowledge are valued.

Qualifications

• 8+ years in software engineering and 3+ years hands-on delivery of ML/AI projects into production.

Responsabilités

• Decide how ML models, generative AI components, data pipelines, and cloud infrastructure work together securely and cost-effectively at scale.
• Architect the entire ecosystem the models live in, beyond just models themselves.
• Focus on system design, stakeholder alignment, risk management, and cross-functional leadership.
• Architect scalable, production-grade AI/ML systems including Retrieval-Augmented Generation (RAG) and real-time inference.
• Select cloud platforms (AWS, Azure, GCP), foundation models, and vector databases.
• Establish CI/CD pipelines, model monitoring, drift detection, data lineage, and regulatory/ethical compliance.
• Translate business goals into technical requirements, lead RFP/RFI responses, and present architecture to executives.
• Collaborate with architects, field teams, vendors, and customer stakeholders.
• Provide governance for upgrades, configurations, integrations, and change activities.
• Ensure compliance with SLAs and KPI performance.
• Drive automation to improve efficiency.
• Identify recurring issues and risks and initiate corrective actions.

Connaissances

Python

PyTorch

TensorFlow

LangChain

LlamaIndex

Pexpect

Outils

MLflow

Kubeflow

Weights & Biases

Apache Spark

Airflow

Feature stores

SageMaker

Description du poste

Join our Team

About this opportunity

An AI/ML Solution Architect designs the end-to-end technical blueprint for artificial intelligence and machine learning systems, bridging the gap between business objectives and engineering execution.

What you will do

• Primary Mission: Decide how ML models, generative AI components, data pipelines, and cloud infrastructure work together securely and cost-effectively at scale.
• Distinction: Unlike data scientists (who build/evaluate models) or AI engineers (who write application code or APIs), architects design the entire ecosystem the models live in.
• Time Allocation: Heavily focused on system design, stakeholder alignment, risk management, and cross-functional leadership.
• Solution Design: Architect scalable, production-grade AI/ML systems including Retrieval-Augmented Generation (RAG), multi-agent orchestration, and real-time inference.
• Technology Selection: Choose appropriate cloud platforms (AWS, Azure, GCP), foundation models (1st-party, 3rd-party, open-source), and vector databases (Pinecone, Milvus, pgvector).
• MLOps & Governance: Establish CI/CD pipelines, model monitoring, drift detection, data lineage, and regulatory/ethical compliance.
• Stakeholder Management and Engagement: Translate vague business goals into technical requirements, lead RFP/RFI responses, and present architecture to executives.

The skills you bring

• Languages & Frameworks: Python, PyTorch, TensorFlow, LangChain, LlamaIndex Pexpect.
• MLOps & Data: MLflow, Kubeflow, Weights & Biases, Apache Spark, Airflow, feature stores.
• Cloud Services: AWS (SageMaker), Azure (Azure ML / AI Search), or Google Cloud (Vertex AI). Certifications (Preferred): AWS Certified Solutions Architect / Machine Learning Specialty, Microsoft Azure AI Engineer/Solutions Architect, or Google Cloud Professional.
• Soft Skills: Problem framing, cross-team orchestration, and executive communication.
• Other Skills: Coordinate across domains to resolve multi-layer technical dependencies.
• Collaborate with architects, field teams, vendors, and customer stakeholders.
• Provide governance for upgrades, configurations, integrations, and change activities.
• Ensure compliance with SLAs and KPI performance.
• Drive automation to improve efficiency.
• Identify recurring issues and risks before impact.
• Initiate corrective actions and process enhancements.
• Stay updated with emerging technologies and industry practices.
• Communicate complex technical issues clearly to leadership and stakeholders.
• Prepare technical reports, RCA summaries, and performance insights.
• Mentor engineers and other teams.
• Telecom Domain knowledge is an added advantage.
• Experience: Typically 8+ years in software engineering and 3+ years hands-on delivery of ML/AI projects into production.

All academic credentials must be from recognized and accredited institutions and are further subject to verification.

All academic credentials must be from recognized and accredited institutions and are further subject to verification.

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.

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