Senior Software Architect

CyberSolve is a fastest growing IAM Specialist firm in the US with poised to become the world's largest company in the IAM space.

Senior Software Architect.

On offer is a role with one of the most powerful IAM teams in the industry, solid projects, competitive salary, ability to expand into other areas of IAM etc. We invite you to join this team.

A detailed Job description for this role is as under:

Job Title: Senior Software Architect

Location:

Experience Level:

Department:

About the Role

hands-on Senior Software Architect

in distributed systems, microservices, data engineering, and security architecture

You will define architectural blueprints, lead engineering design reviews, implement core components, and ensure the platform’s scalability, resilience, and compliance in hybrid-cloud environments.

Key Responsibilities

1. Architecture Ownership

• Architect, design, and validate a

  7-tier distributed architecture

  spanning ingestion, streaming, correlation, analytics, APIs, and presentation layers.
• Define and maintain system-wide

  logical, physical, and data architectures

  , ensuring modularity and scalability across microservices.
• Translate complex business requirements into

  domain-driven design models

  and well-defined service boundaries.

2. Technical Design & Development

• Lead by example: design and develop

  Spring Boot microservices

  , data processing pipelines, and core APIs.
• Define best practices for

  event-driven and reactive architectures

  using

  Kafka, WebFlux, and Redis.

• Oversee design of the

  Angular-based UI

  , ensuring seamless integration via REST/GraphQL APIs and secure OIDC authentication.
• Optimize data flow across PostgreSQL, ElasticSearch, Neo4j, and S3/Object Store.

3. Agentic AI Integration

• Architect and implement Agentic AI modules that autonomously analyze data, detect risk patterns, and recommend remediation.
• Collaborate with AI/ML teams to integrate LangChain4J, OpenAI API, or Vertex AI models into backend workflows.
• Define autonomous orchestration loops where AI agents trigger correlation, policy tuning, or connector optimization.
• Drive innovation in AI observability — ensuring transparency, explainability, and compliance of AI-driven actions.

4. Vibe Coding & AI-Augmented Engineering

• Leverage vibe coding skills — advanced proficiency in collaborating with AI coding assistants (e.g., GPT-5, Copilot, CodeWhisperer) for rapid prototyping and code generation.
• Establish patterns and best practices for AI pair programming, agentic code scaffolding, and autonomous test generation.
• Mentor teams on how to effectively integrate AI tools into development, CI/CD, and data pipelines to accelerate delivery.
• Lead by example through hands-on, AI-assisted coding sessions to drive productivity and innovation.

5. Data Engineering & AI Integration

• Design robust

  data ingestion and correlation pipelines

  using Kafka, Spark, and Flink.
• Integrate ML models (e.g., anomaly detection, risk scoring) into real-time workflows using Python-based services.
• Collaborate with data scientists to operationalize ML models for access risk prediction and anomaly detection.
• Govern

  schema evolution and data lineage

  through Kafka Schema Registry and version-controlled ETL processes.

6. Security, Compliance & Governance

• Enforce

  Zero Trust

  principles across all tiers: mutual TLS, JWT authentication, and least-privilege service accounts.
• Integrate with

  Vault, Keycloak,

  and

  OPA

  for secrets management, identity federation, and policy enforcement.
• Define architecture for

  immutable audit logging

  and compliance zones (SOX, HITRUST, NIST).

7. Integration Leadership

• Architect and oversee integrations with variety of cloud and on-premises solutions.
• Standardize connector SDKs, webhooks, and SCIM/Syslog ingestion patterns.
• Define API governance, versioning, and documentation standards (OpenAPI/Swagger, GraphQL schemas).

8. DevOps, Observability & Performance

• Define CI/CD pipelines using

  GitLab/Jenkins/ArgoCD

  for continuous integration and deployment.
• Establish observability with

  Prometheus, Grafana, and OpenTelemetry

  ; define SLOs and performance KPIs.
• Design for resilience: implement horizontal scaling, async retry mechanisms, caching, and partitioning strategies.

9. Leadership & Mentorship

• Mentor a cross-functional team of backend, frontend, and data engineers.
• Conduct design and code reviews, ensuring architectural consistency and technical excellence.
• Partner with product management and stakeholders to align technical roadmaps with business vision.

Required Technical Skills

Core Architecture & Development

• Strong command of

  Java 17+, Spring Boot 3.x, Spring Cloud, Spring WebFlux

• Proficiency in

  Angular 16+/TypeScript, NgRx, RxJS

• Experience with

  Kafka, Redis, PostgreSQL, Elasticsearch, Neo4j, S3/Azure Blob

• Deep understanding of

  microservices, event-driven

  , and

  domain-driven architectures

• AI & Agentic Systems
• Hands-on experience integrating LLMs (OpenAI / Vertex / LangChain4J) into production-grade systems.
• Knowledge of autonomous agent frameworks, AI toolchains, and vector databases.
• Proven proficiency in vibe coding — leveraging AI pair programmers for design, code, and documentation.

Data & Analytics

• Proficient with

  Apache Kafka Streams / Flink / Spark for ETL

  and

  stream processing

• Familiarity with

  ML model integration (Python, REST, or LangChain4J)

• Knowledge of

  graph analytics

  and

  identity correlation models

Security & Compliance

• Expertise in

  OAuth2, OIDC, SAML, and Keycloak

• Hands-on with

  Vault, OPA, TLS/mTLS, RBAC, audit logging

• Knowledge of

  Zero Trust, IAM/PAM/IGA ecosystems

  , and regulatory frameworks

Cloud & DevOps

• Experience deploying to

  AWS EKS / Azure AKS, with Kubernetes, Docker

  , and

  Helm

• CI/CD automation via

  Jenkins, GitLab CI, or ArgoCD

• Observability stack:

  Prometheus, Grafana, ELK, OpenTelemetry

Preferred Experience

• 12+ years in software engineering, including 5+ as a principal or lead architect.
• Experience designing

  AI-augmented enterprise SaaS platforms

  or

  security analytics ecosystems.

• Background in

  data engineering, agentic AI systems

  , and

  hybrid-cloud architecture

  .
• Strong communication, mentorship, and cross-functional collaboration skills.