Hi,
We are having an immediate requirement for the below mentioned role:
Solutions Architect (Principal Digital Architect AI / GenAI)
we
Job Summary
We are looking for an experienced Principal Digital Architect AI / GenAI to lead the end-to-end architecture of complex enterprise AI and digital platforms.
The ideal candidate will have strong experience designing large-scale distributed systems, AI/GenAI architectures, RAG solutions, Agentic AI workflows, cloud-native platforms, APIs, data architecture, DevOps, and enterprise integration.
This position requires regular collaboration with business owners, product teams, engineering leaders, and architecture teams located in the U.S.
Experience Required
Bachelor's degree with 5+ years of relevant experience required
Preferred: 10 15+ years of overall IT experience
Strong experience in Solution Architecture, Application Architecture, Platform Architecture, or Enterprise Architecture
Hands-on experience architecting and productionizing AI/ML and Generative AI solutions
Key Responsibilities
Own and define end-to-end solution and platform architecture for enterprise-scale AI and distributed applications from concept through production.
Design highly scalable, secure, resilient, performant, and cost-efficient architectures.
Translate complex and ambiguous business requirements into durable technical solutions.
Collaborate with business leaders, product owners, engineering managers, developers, and architecture teams.
Define and maintain AI reference architectures, architectural patterns, standards, and best practices.
Evaluate new technologies and conduct proofs of concept, prototypes, and architectural spikes.
Guide engineering teams through architectural decisions, design reviews, and implementation challenges.
Evaluate architectural trade-offs across traditional software, classical Machine Learning, LLM-based solutions, RAG, and Agentic AI.
Ensure architectures comply with enterprise security, privacy, regulatory, and governance requirements.
Produce architecture diagrams, design documentation, decision records, and technical trade-off analysis.
Improve platform reliability, developer productivity, observability, scalability, and infrastructure cost efficiency.
Mentor technical teams and provide architectural leadership across multiple initiatives.
Required Technical Skills
Strong Solution Architecture / Platform Architecture / Application Architecture expertise
Enterprise-scale distributed systems architecture
Strong programming knowledge in Python and Java
Cloud-native architecture, preferably AWS
Docker and Kubernetes
Microservices and event-driven architectures
Strong API architecture experience with:
REST
GraphQL
gRPC
API versioning, integration, security, and documentation
Strong understanding of:
SQL
NoSQL databases
Data modeling
Replication
Sharding
Data warehouses
Snowflake
Modern DevOps practices including:
CI/CD
Infrastructure as Code
Automated testing
Observability
Monitoring
AI / Generative AI Architecture Skills
Strong hands-on experience designing enterprise Generative AI and RAG architectures, including:
Data ingestion pipelines
Document preprocessing
Chunking strategies
Embedding generation
Vectorization
Similarity search
Query-time retrieval
Ranking and reranking
Context assembly
Vector databases and semantic search platforms
Must understand RAG design trade-offs involving:
Embedding dimensions
Chunk size
Chunk overlap
Retrieval quality
Recall
Latency
Performance
Token consumption
Cost optimization
Agentic AI & LLM Skills
Experience with Agentic AI frameworks and multi-step AI workflows
Prompt engineering and prompt versioning
Context management
Conversation memory and AI memory patterns
Model routing
Model fallback strategies
LLM orchestration
AI workflow integration with enterprise systems
API and event-driven AI integrations
Strong understanding of:
Hosted vs. self-hosted LLMs
Fine-tuning vs. RAG vs. hybrid approaches
Model selection
LLM evaluation
AI monitoring
Drift detection
Guardrails
AI security
Data privacy
Performance and latency optimization
Token efficiency
AI cost controls
Preferred Qualifications
Experience defining enterprise AI reference architectures and standards
Proven experience taking AI solutions from POC/prototype to enterprise-scale production
Experience assessing and adopting emerging AI technologies
Strong architectural decision-making and trade-off analysis skills
Ability to influence technical teams without direct authority
Excellent communication skills with both technical and non-technical stakeholders
Ability to communicate architectural recommendations clearly to U.S.-based business and technology teams
Key Skills / Keywords
Principal Architect, Digital Architect, AI Architect, GenAI Architect, Solution Architect, Enterprise Architect, RAG, Generative AI, LLM, Agentic AI, Python, Java, AWS, Kubernetes, Docker, Snowflake, Vector Database, Embeddings, Semantic Search, REST API, GraphQL, gRPC, Microservices, Distributed Systems, SQL, NoSQL, CI/CD, Infrastructure as Code, Observability, AI Governance, AI Security