AI Solution Architect
AI Solution Architect
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Job Description
Qualifications and Education Requirements: Must Have: Engineering graduate with 15 years of experience in Enterprise Applications development. Experience in designing AI applications and knowledge of machine learning frameworks like TensorFlow or PyTorch. Design develop and oversee the implementation of endtoend AI solutions. Selfstarter with an indepth handson work experience with largescale implementations on AWS or Azure. Knowledgeable on Google Cloud Platform. Hands on expertise in design applications using Enterprise Architectural Patterns. Expertise in fullstack development using technologies such as Python Java C# Angular React. Should have working exposure in tools like Rally Jira Collobrator Coverity Valgrind tools. Experience helping development teams build and deploy micro servicesbased applications in public cloud Experience with Continuous Integration & Continuous Deployment tools and processes. Should be very good in Verbal & Written Communication. Cloud Platform Expertise: Handson experience with one or more of the following cloud platforms and their AI/ML tools: o AWS: Expertise with services like Amazon SageMaker AWS Bedrock AWS Lambda Amazon S3 Amazon EC2 SageMaker Model Registry and AWS Glue for data engineering and model deployment. o Azure: Expertise with services like Azure AI Studio Azure Machine Learning Azure AI Search GPT Azure Kubernetes Service (AKS) Azure Cognitive Services Azure Functions and Azure Machine Learning Model Registry.
o Google Cloud: Expertise with services like GCP Vertex AI GCP Vertex AI Generative AI Studio Gemini TensorFlow Extended (TFX) Google Kubernetes Engine (GKE) BigQuery Cloud Functions and Vertex AI Model Registry. Generative AI Expertise: Experience with Generative AI models including text generation (e.g. GPT) image generation (e.g. DALLE) or other creative models leveraging cloudnative tools such as AWS Bedrock Azure AI Studio GCP Vertex AI Generative AI Studio GPT Gemini RAG techniques like Langchain Vector Database like Chroma DB Pinecone etc. MLOps Implementation: Proficient in MLOps workflows including model training deployment monitoring versioning and automation. Experience with tools such as MLflow Kubeflow Terraform Jenkins and Docker. Model Registry & Versioning: Experience with model registry services like SageMaker Model Registry Azure Machine Learning Model Registry and Vertex AI Model Registry to track and govern models throughout their lifecycle. Data Engineering & Big Data: Proficiency in data engineering best practices data pipeline design and management of big data infrastructure in cloud environments including tools like Apache Kafka Apache Spark AWS Glue Azure Data Factory and Google Cloud Dataflow. DevOps & Cloud Infrastructure: Familiarity with DevOps principles and infrastructureascode (IaC) tools like Terraform CloudFormation and Kubernetes for managing cloud infrastructure. Security & Compliance: Deep understanding of cloud security principles including IAM data encryption and governance best practices. Programming & AI Frameworks: Strong programming skills in languages such as Python Java or R and experience with AI/ML libraries and frameworks (e.g. TensorFlow PyTorch Keras Scikitlearn). PREFERRED SKILLS Experience in Google Cloud Platform Experience of working in Media and Communication / broadcast business domain ADDITIONAL NOTES Certification in AI and Architecture area is plus.
Job Title: Hi Applicants!!! Hiring for a Job in a Reputed Organization(Product and Service based company). Here is a Gateway to it through ALP Consulting. Recruiting Employment Type: Permanent Experience: Skills Required: Excellent Communication Skills Strong Experience in : Job Location: Pan India Note: Maximum 60 Days Notice Period will be Prioritized.
Employment Type
Full Time
