AI Solution Architect

TechDigital Group; Holmdel Township (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

TechDigital Group is seeking a senior Enterprise Architect to lead complex programs across business domains and technology stacks, focusing on GenAI, AI-driven transformations, and stakeholder alignment.

The role requires deep architecture discipline coverage, cloud platforms, and hands-on proficiency with polyglot stacks, APIs, and modern DevOps practices to guide secure, scalable solutions.

Qualifications

• 15+ years of enterprise software engineering and architecture experience.
• Proven track record as a Solution Architect or Enterprise Architect across large-scale programs spanning multiple business domains and technology stacks.
• Extensive experience leading digital and AI-driven transformation programs, including stakeholder management.

Skills

Enterprise architecture

GenAI & Agent Technologies

Solution architecture

Stakeholder management

Cloud platforms

Polyglot tech design

APIs & service mesh

DevOps & platform engineering

RAG pipelines & knowledge graphs

LangChain/LangGraph/AutoGen

Education

Bachelor's degree in CS/SE

Master's degree in CS/SE

Related technical discipline

Tools

LangChain

LangGraph

CrewAI

AutoGen

MCP Protocol

OpenAI GPT-4o

Azure OpenAI

AWS Bedrock

Terraform

Kubernetes

Istio

Apache Kafka

PostgreSQL

Cosmos DB

Oracle

Job description

Job Description

• 15+ years of enterprise software engineering and architecture experience with a bachelor's or master's degree in computer science, Software Engineering, or a related technical discipline
• Proven track record as a Solution Architect or Enterprise Architect across large-scale, complex programs spanning multiple business domains and technology stacks
• Extensive experience leading digital and AI-driven transformation programs, including stakeholder management.

Generative AI & Agent Technologies (2+ Years)

• Hands‑on experience architecting and building GenAI Agent solutions using LangChain, LangGraph, CrewAI, AutoGen, or MCP Protocol
• Strong knowledge of LLM APIs: Anthropic Claude, OpenAI GPT‑4o, Azure OpenAI — including model selection, context management, and cost optimization
• Experience designing enterprise‑grade Retrieval‑Augmented Generation (RAG) pipelines, vector stores and knowledge graph integrations
• Proficiency in prompt engineering techniques: Chain‑of‑Thought, few‑shot/zero‑shot strategies, and responsible‑AI guardrails
• Exposure to cloud AI platforms: AWS Bedrock

Solution & Enterprise Architecture

• Deep expertise in solution architecture disciplines: capability modelling, application architecture, integration architecture, data architecture, and security architecture
• Hands‑on experience defining target‑state architectures, architecture roadmaps, and transition architectures aligned to business strategy
• Proficiency with architecture frameworks and methodologies: TOGAF, Zachman, or equivalent enterprise architecture frameworks
• Extensive experience with integration patterns: event‑driven architecture (EDA), API‑led connectivity, microservices, CQRS, and Saga patterns
• Strong understanding of cloud architecture principles across AWS, Azure, or GCP — including multi‑cloud and hybrid strategies
• Experience governing architecture across programs: Architecture Review Boards (ARB), design authority participation, and architecture decision records (ADR)

Technology Stack (Hands‑On Proficiency)

• Java / J2EE: Java 11–21, Spring Boot, Spring Framework, Jakarta EE, microservices with REST/gRPC, Apache Kafka, JPA/Hibernate, PostgreSQL, Oracle
• .NET: C# (.NET 6/7/8), ASP.NET Core Web API, Entity Framework Core, Azure Service Bus, Dapper, SQL Server, and Cosmos DB
• Strong ability to design and review polyglot architectures spanning both Java and .NET ecosystems, selecting the right stack for each capability
• Hands‑on experience with API gateway and service mesh technologies: Kong, Apigee, AWS API Gateway, MuleSoft, or Istio
• Familiarity with frontend frameworks (React, Angular) and mobile patterns sufficient to define end‑to‑end solution architectures

DevOps & Platform Engineering (Exposure & Understanding)

• Good understanding of CI/CD pipeline design using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps — able to define standards and review pipeline architectures
• Working knowledge of containerization and orchestration: Docker, Kubernetes (EKS, AKS, GKE), Helm, and Istio service mesh
• Understanding of Infrastructure‑as‑Code: Terraform, AWS CloudFormation, or AWS CDK for cloud provisioning governance
• Familiarity with observability stacks: AWS CloudWatch, Prometheus, Grafana, ELK Stack — able to define non‑functional requirements and monitoring strategies
• Appreciation of DevSecOps practices: SAST/DAST tooling, secrets management (HashiCorp Vault, AWS Secrets Manager), and shift‑left security in the SDLC

Transformation Program & Stakeholder Management

• Experience in the life insurance domain: underwriting, claims processing, policy administration, or actuarial tooling
• Knowledge of insurance regulatory and data‑governance standards (SOX, GDPR equivalents)

Solution Architecture & SDLC Transformation

• Experience in the life insurance domain: underwriting, claims processing, policy administration, or actuarial tooling
• Knowledge of insurance regulatory and data‑governance standards (SOX, GDPR equivalents)

Domain Experience

• Experience in the life insurance domain: underwriting, claims processing, policy administration, or actuarial tooling
• Knowledge of insurance regulatory and data‑governance standards (SOX, GDPR equivalents)