V
Architect
Job Description
Job Requirements
Hands-on Experience: Proven track record in building and deploying AI agents using frameworks such as LangChain, Strands, or cloud-native ADKs (Agent Development Kits).CSP Foundation Models: Practical experience working with major Cloud Service Provider(CSP) AI ecosystems (e.g., AWS Bedrock,Agentcore,).Agent Capabilities: Deep knowledge of agentic architecture patterns (ReAct, multi-agent coordination, tools/function calling, memory retention, and RAG architectures)Multi-Cloud Exposure: Hands-on experience navigating and deploying into at least one primary cloud provider (AWS, with general operational knowledge across a multi-cloud estate.Infrastructure as Code (IaC): Proficient in writing modular, reusable Terraform scripts for cloud infrastructure management.DevOps Practice: Experience configuring CI/CD pipelines (e.g., GitHub Actions, GitLab CI,Azure DevOps, Jenkins) for both standard application code and AI/ML artifacts.Problem Solver: Proven ability to rapidly build POCs from rough business requirements to prove technical feasibility.Collaborative Team Player: Excellent communication skills with a track record of actively collaborating with competency centers, engineering leads, and business teams.Experience with vector databases (e.g., Pinecone, Qdrant, S3 vector database).hadn on expertise with Docker, Kubernetes, or serverless execution models (AWS Lambda)for lightweight agent hosting.Exposure to agent monitoring, evaluation frameworks, and LLM observability tools Core Languages: Strong proficiency in Java or .NET (C#) for writing core enterprise service layers and microservice SDLC Discipline: Full-lifecycle experience, including system design, unit testing, automated integration testing, and code reviews
Infrastructure & MigrationInfrastructure Migration: Proven experience executing large-scale servermigrations using AWS Application Migration Service (MGN) and database migrations using AWS Database Migration Service (DMS).Migration Discovery and Planning: Skilled in leveraging AWS Transform for automated portfolio discovery, dependency mapping, and migration wave planning.Cloud Foundation: Proficient in designing and deploying secure AWS Landing Zones, including VPC networking, IAM, and automated governance guardrails.VMware Virtualization and Migration: Extensive experience with VMware vSphere/ESXi environments and familiarity with migration tools such as VMware HCX for seamless workload mobility to AWS.Migration Patterns
Work Experience
5-7Years
Hands-on Experience: Proven track record in building and deploying AI agents using frameworks such as LangChain, Strands, or cloud-native ADKs (Agent Development Kits).CSP Foundation Models: Practical experience working with major Cloud Service Provider(CSP) AI ecosystems (e.g., AWS Bedrock,Agentcore,).Agent Capabilities: Deep knowledge of agentic architecture patterns (ReAct, multi-agent coordination, tools/function calling, memory retention, and RAG architectures)Multi-Cloud Exposure: Hands-on experience navigating and deploying into at least one primary cloud provider (AWS, with general operational knowledge across a multi-cloud estate.Infrastructure as Code (IaC): Proficient in writing modular, reusable Terraform scripts for cloud infrastructure management.DevOps Practice: Experience configuring CI/CD pipelines (e.g., GitHub Actions, GitLab CI,Azure DevOps, Jenkins) for both standard application code and AI/ML artifacts.Problem Solver: Proven ability to rapidly build POCs from rough business requirements to prove technical feasibility.Collaborative Team Player: Excellent communication skills with a track record of actively collaborating with competency centers, engineering leads, and business teams.Experience with vector databases (e.g., Pinecone, Qdrant, S3 vector database).hadn on expertise with Docker, Kubernetes, or serverless execution models (AWS Lambda)for lightweight agent hosting.Exposure to agent monitoring, evaluation frameworks, and LLM observability tools Core Languages: Strong proficiency in Java or .NET (C#) for writing core enterprise service layers and microservice SDLC Discipline: Full-lifecycle experience, including system design, unit testing, automated integration testing, and code reviews
Infrastructure & MigrationInfrastructure Migration: Proven experience executing large-scale servermigrations using AWS Application Migration Service (MGN) and database migrations using AWS Database Migration Service (DMS).Migration Discovery and Planning: Skilled in leveraging AWS Transform for automated portfolio discovery, dependency mapping, and migration wave planning.Cloud Foundation: Proficient in designing and deploying secure AWS Landing Zones, including VPC networking, IAM, and automated governance guardrails.VMware Virtualization and Migration: Extensive experience with VMware vSphere/ESXi environments and familiarity with migration tools such as VMware HCX for seamless workload mobility to AWS.Migration Patterns
Work Experience
5-7Years
More Info
Key Skills
AWS Bedrock
VMware HCX
AWS Database Migration Service
Qdrant
vector databases
Pinecone
memory retention
Agentcore
GitHub Actions
S3 vector database
multi-agent coordination tools
RAG architectures
LangChain
AWS Application Migration Service
AWS Transform
ADKs Agent Development Kits
GitLab CI
CI/CD pipelines
function calling
About Company
Skills:
data engineering , Java, Pyspark, Etl Tools, Python, Gcp, Azure, AWS, LangChain, prompt engineering, Claude 2, Chroma, Open AI GPT, FAISS, PaLM 2, Pinecone, Cohere, Dolly
Skills:
Java, Machine Learning, Database Administration, Devops, Docker, Azure, Python, Kubernetes, AWS, GenAI, LLMs, semantic technologies, event-driven patterns, intelligent automation frameworks, microservices architecture, RAG, CI/CD, API-first design principles, Knowledge Graphs, Enterprise Software Engineering
Skills:
PowerShell, Networking, Terraform, Data Governance, Python, Modeling, Infrastructure as Code, data architecture fundamentals, API and event-driven architecture, master and reference data, identity and security controls, analytics platform patterns, Azure PaaS and SaaS services, enterprise integration patterns, automation tooling, core networking concepts
Skills:
Spring Boot, Kafka, Sql, Nosql, Docker, Terraform, Kubernetes, Apm, Ddd, CQRS, Event Sourcing, CI/CD, real-time processing, Java 11+, chaos engineering
Skills:
Retrieval-Augmented Generation (RAG) pipelines, Large Language Models (LLMs), Gcp, Docker, FastAPI, Azure, Python, Kubernetes, LangChain, vector databases