AWS Architect
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Job Summary
AWS Solutions Architect AI (Bedrock & SageMaker)
Experience: 8 10 Years
Education: Bachelors or Masters degree in Computer Science Information Technology Artificial Intelligence or a related field.
Job Summary
We are looking for an experienced AWS Architect with strong expertise in designing implementing & deploying cloud-native AI/ML & Generative AI solutions on AWS. The ideal candidate will have hands-on experience with Amazon Bedrock Amazon SageMaker AWS AI services & modern cloud architecture. The role involves working closely with business stakeholders & engineering teams to build efficient AI applications.
Key Responsibilities
- Design & implement scalable cloud solutions using AWS services.
- Architect AI & Generative AI applications using Bedrock & foundation models.
- Build train deploy & monitor machine learning models using SageMaker.
- Design Retrieval-Augmented Generation (RAG) architectures.
- Integrate Large Language Models (LLMs) with enterprise applications.
- Develop AI-powered copilots document intelligence & management solutions.
- Design secure APIs using API Gateway Lambda ECS/EKS & containerized microservices.
- Implement vector databases such as OpenSearch Pinecone.
- Optimize AI workloads for performance scalability & cost.
- Establish CI/CD pipelines for ML & cloud deployments.
- Implement security best practices IAM policies encryption & governance.
- Work with cross-functional teams to translate business requirements into technical solutions.
Required Skills
AWS Cloud
- AWS Solution Architecture
- VPC
- EC2
- Lambda
- ECS
- EKS
- S3
- IAM
- CloudFormation / CDK
- API Gateway
- CloudWatch
- Step Functions
- EventBridge
- SNS/SQS
AI / Machine Learning
- Amazon Bedrock
- Amazon SageMaker
- Prompt Engineering
- Fine-tuning foundation models
- Model deployment
- Feature Store
- Model Monitoring
- ML Pipelines
Generative AI
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Embeddings
- Vector Databases
- Prompt Engineering
- Agentic AI
- AI Guardrails
- Model Evaluation
Programming
- Python
- SQL
- Java or (preferred)
Databases
- DynamoDB
- Aurora
- PostgreSQL
- OpenSearch
- Redis
DevOps
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- Jenkins
- CodePipeline
Preferred Qualifications
- AWS Certified Solutions Architect Professional or Associate
- AWS Certified Machine Learning Specialty
- Experience with Generative AI frameworks such as LangChain LlamaIndex or Semantic Kernel
- Experience integrating OpenAI Anthropic Claude Meta Llama or Amazon Nova models through Amazon Bedrock
- Knowledge of MLOps best practices
- Experience building enterprise AI solutions
Desired Candidate Profile
The ideal candidate should demonstrate:
- Strong cloud architecture & solution design skills
- Experience delivering production-grade AI/ML solutions
- Excellent understanding of AWS Well-Architected Framework
- Strong communication & stakeholder management skills
- Ability to lead technical discussions & mentor development teams
- Problem-solving & analytical mindset
Required Skills:
About Company: Pratiti Technologies creates impactful digital experiences that fuel innovation across industries. With its headquarters in Pune and offices in the USA UAE and India Pratiti is recognized for engineering excellence and a culture that inspires people to explore innovate and grow. Specializing in Cloud Edge Computing Industrial IoT Data Science and AR/VR we partner with global clients to transform bold ideas into real-world products. At Pratiti youll be part of a team of technology craftsmen who value ownership creativity and collaboration. AI Architect - Associate (8 Years of Total Experience) Proven Delivery: Lead the end-to-end lifecycle of complex AI projects moving beyond prototypes to deliver robust production-grade industrial solutions. Advanced AI Orchestration: Architect sophisticated Agentic AI systems and advanced RAG pipelines utilizing Knowledge Graphs for context-aware reasoning. Model Optimization: Demonstrate deep expertise in Python and the fine-tuning of LLMs to tailor model performance for specific domain requirements. Modern Full-Stack: Build high-performance scalable backends using FastAPI and lead full-stack development to ensure seamless integration of AI features. Technical Governance: Own the technical roadmap by delivering rigorous High-Level (HLD) and Low-Level Designs (LLD) that ensure system scalability. Cloud Native: Design and deploy secure resilient architectures on AWS leveraging cloud-native services to support heavy AI workloads. Domain Expertise: Apply your experience in PLM or Manufacturing to solve real-world industrial challenges at the intersection of digital and physical worlds. Engineering Excellence: Drive best practices in CI/CD code quality and security ensuring that AI solutions meet the highest enterprise standards. Visionary Leadership: Act as a hands-on technical mentor bridging the gap between cutting-edge AI research and practical value-driven engineering.
