We are looking for an experienced Solutions Architect – AI & Platforms who can translate business requirements into scalable and secure technology solutions. The role requires strong expertise in modern software architecture, cloud-native platforms, and AI/LLM-based systems.
The ideal candidate will work closely with business stakeholders, product teams, and engineering teams to design and implement robust solutions leveraging both traditional software engineering practices and emerging AI technologies.
ROLES & RESPONSIBILITIES :
– Design and implement AI-driven solutions leveraging Language Models (LLMs/SLMs), ML models.
– Design AI solution patterns including Retrieval-Augmented Generation (RAG), AI agents, semantic search, and document processing systems.
– Evaluate and integrate open-source and proprietary AI models based on performance, cost, and deployment constraints.
– Architect scalable AI solutions and services supporting model serving, inference pipelines, and AI-powered applications.
– Provide architectural guidance to engineering teams during implementation and ensure alignment with architectural principles.
– Ensure systems are designed for scalability, reliability, security, and performance.
– Drive adoption of best practices in software engineering, DevOps, and cloud architecture.
– Participate in technical reviews and design governance.
– Mentor engineering teams on modern architecture and AI-enabled development practices.
– Work closely with product managers, business stakeholders, and engineering teams to refine technical solutions.
– Ensure responsible AI practices, including data privacy, security, and governance when deploying AI systems.
SKILLS & REQUIREMENTS :
– Minimum 10+ years of experience in software engineering, system architecture, or platform engineering and minimum 1+ years of experience in AI solutioning.
– Proven hands-on experience in developing and productionizing AI based solution.
– Strong foundation in Machine Learning, LLMs, and modern AI architectures.
– Solid experience in system design and architecture trade-offs (performance, scalability, cost, reliability).
– Hands-on experience with microservices architecture, API design, and event-driven systems.
– Familiarity with data architecture and data pipelines using tools such as Apache Spark, Airflow, Prefect, Dagster, or Kafka-based pipelines will be added advantage.
– Familiarity with model serving and inference frameworks such as Ollama/TensorFlow Serving/ Triton Inference Server/vLLM.
– Familiarity with MLOps / LLMOps practices, including model deployment, monitoring, and lifecycle management, including tools such as MLflow, Kubeflow, Weights & Biases.
– Strong programming experience in Python (preferred) or Java, Node.js, or C#.
– Strong foundation in containerization and exposure to deployment of containerized application on production environment
– Experience with vector databases and semantic search systems such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, or Elasticsearch/OpenSearch will be an added advantage.
– Strong understanding of DevOps practices, CI/CD pipelines, and code review workflows using tools such as Git, GitHub/GitLab, Jenkins, GitHub Actions, or ArgoCD.
– Any exposure to AI evaluation frameworks, guardrails, and model monitoring will be added advantage
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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