Senior Solutions Architect

About the Role

We are looking for a Solution Architect with 10–15 years of experience to design scalable, secure, and cloud-ready solutions. The role involves working with customers, Senior Solution Architects, business analysts, project managers, and engineering teams across cloud, modernization, microservices, integration, and digital transformation initiatives.

Must Have Skills

• 10–15 years of experience in software development, architecture, and enterprise application delivery.
• Strong experience with Azure and/or AWS and cloud-native architecture.
• Hands-on experience with Microservices, REST APIs, SOA, and system integration.
• Experience in application modernization and cloud migration.
• Knowledge of Docker, Kubernetes, CI/CD, and Infrastructure as Code.
• Understanding of cloud security, IAM, networking, monitoring, and disaster recovery.
• Ability to create architecture diagrams, solution designs, and technical documentation.
• Strong analytical, communication, and customer-facing skills.

Good To Have Skills

• AWS/Azure certifications.
• Experience with Serverless, Event-Driven Architecture, Messaging, and API Management.
• Exposure to SaaS / Multi-Tenant Architecture.
• Knowledge of Generative AI and AI-enabled solutions.
• Experience with pre-sales, POCs, estimations, and technical proposals.
• Exposure to application security and compliance.
• Experience working with global customers and distributed teams.

Responsibilities

• Design end-to-end solutions and independently own defined architecture workstreams.
• Translate business and technical requirements into application, cloud, integration, and deployment designs.
• Define microservice, API, integration, and data-flow architectures.
• Guide engineering teams on architecture implementation and conduct design/code reviews.
• Contribute to cloud migration, modernization, and digital transformation initiatives.
• Participate in customer workshops, technical discussions, POCs, and solution demonstrations.
• Identify and address architectural, performance, security, and technical risks.
• Ensure solutions follow defined architecture, security, and engineering standards.
• Work closely with the Senior Solution Architect on complex and strategic engagements.
• Develop reusable architecture patterns, templates, and technical accelerators

Next

About the Role

Antier Solutions is looking for a technically strong AI Solution Architect to drive the architecture, design, and technical execution of AI-powered solutions.

The role requires a combination of deep technical expertise, architectural ownership, and the ability to guide engineering teams in building scalable, production-ready AI systems. The individual will evaluate business problems, define technical approaches, make architecture decisions, and work closely with developers and stakeholders to translate ideas into working solutions.

This is a hands-on architecture and technical leadership role, not one limited to documentation, project coordination, or pre-sales presentations.

Key Responsibilities

1. AI Architecture & Solution Design

• Design end-to-end architectures for AI, Generative AI, LLM-based applications, and agentic AI systems.
• Evaluate and select appropriate models, frameworks, orchestration approaches, and technology stacks.
• Design solutions involving RAG, AI agents, workflow automation, APIs, databases, and enterprise integrations.
• Define architecture standards covering scalability, security, performance, maintainability, and deployment.
• Evaluate technical feasibility, identify risks, and recommend practical implementation approaches.

2. Technical Leadership & Implementation

• Provide architectural direction and technical guidance to AI engineers and developers.
• Review proposed designs and implementation approaches, identifying technical gaps and potential bottlenecks.
• Establish reusable architecture patterns, development standards, and engineering best practices.
• Troubleshoot complex technical challenges and contribute hands-on where necessary.
• Guide teams in adopting AI-assisted development and agentic workflows where they improve engineering productivity.

3. Production Readiness & Quality

• Design solutions with appropriate authentication, access controls, logging, monitoring, testing, and evaluation mechanisms.
• Address AI-specific challenges such as hallucinations, retrieval quality, model selection, latency, reliability, and inference costs.
• Define appropriate human oversight and validation mechanisms for sensitive or consequential workflows.
• Guide deployment decisions across suitable cloud, on-premise, and hybrid environments.

4. Business Alignment & Delivery Ownership

• Understand business requirements and translate them into implementable technical solutions.
• Work with stakeholders to establish scope, dependencies, estimates, resource requirements, and delivery milestones.
• Collaborate with engineering and delivery teams to move solutions from proof of concept to production.
• Balance rapid execution with architectural quality, maintainability, and commercial feasibility.
• Communicate technical decisions, risks, and trade-offs clearly to business and technical stakeholders.

Required Skills & Experience

• B.Tech, BE, MCA, MSc, or equivalent technical qualification in Computer Science, IT, Data Science, or a related discipline.
• 8+ years of overall experience in software engineering, AI engineering, solution architecture, or related technical roles.
• Strong hands-on experience building AI/ML or Generative AI applications, with demonstrated responsibility for architecture and implementation decisions.
• Strong understanding of LLMs, RAG pipelines, agentic AI systems, tool calling, orchestration, and AI-driven automation.
• Experience with Python and relevant AI frameworks, libraries, and integration technologies.
• Strong understanding of APIs, databases, data pipelines, distributed systems, and application architecture.
• Experience evaluating AI solutions for accuracy, reliability, performance, security, and cost.
• Ability to guide developers, review technical approaches, resolve complex problems, and establish reusable engineering practices.
• Experience deploying or supporting AI applications in production environments.
• Strong analytical, communication, and technical decision-making skills.

Preferred Qualifications

• Experience architecting multi-agent systems or complex AI automation workflows.
• Exposure to cloud platforms, containerization, CI/CD, observability, and scalable AI infrastructure.
• Experience mentoring engineering teams and introducing new AI development practices.
• Experience with enterprise AI deployments, international clients, or technically complex business environments.

Ideal Candidate Profile

• We are looking for an individual who can independently own technical architecture, guide engineering teams, and make sound implementation decisions. The candidate should combine hands-on AI expertise with the ability to turn business requirements into scalable, production-ready solutions.
• Candidates whose experience is limited to AI research, business analysis, project coordination, or pre-sales documentation without meaningful technical implementation and architecture ownership may not be suitable.

AI Solution Architect

Experience: 12+ Years

Location: Coimbatore / Hybrid

Joining: Immediate / Within 30 Days

Primary Skills: Enterprise Architecture, Python, REST APIs, Microservices, Distributed Systems, Cloud (AWS/Azure/GCP), CI/CD, Docker, Kubernetes, Enterprise Data Architecture, Integration Patterns.

Preferred Skills: LLM Integrations, RAG Pipelines, AI Agents, Agentic Workflows, MCP (Model Context Protocol), Vector Databases, Prompt Engineering, LangChain/LlamaIndex, LLMOps, Multi-Agent Orchestration.

About the Role

At Techjays, we're helping companies reimagine how they build, operate, and scale with AI at the core. We focus on building secure, scalable, production-grade AI systems that solve real business problems and deliver measurable outcomes.

We're looking for an AI Solution Architect who can own enterprise-level solution architecture end-to-end. The ideal candidate combines deep technical expertise with the ability to understand complex business challenges, engage with prospective clients, and design compelling, scalable, AI-native solutions.

This is a senior technical role at the intersection of enterprise architecture, pre-sales, solutioning, and delivery governance. You'll collaborate with leadership, engineering teams, and clients to architect solutions spanning AI integrations, RAG pipelines, agentic workflows, cloud infrastructure, and enterprise platforms.

This role requires a strong technical background and current hands-on expertise. Candidates with purely pre-sales experience or non-technical solutioning backgrounds will not be a fit.

Key Responsibilities

• Own end-to-end enterprise architecture for AI-native platforms, defining high-level and low-level designs across backend systems, data platforms, and AI components.
• Lead solutioning for complex enterprise engagements, translating client requirements into technically sound, secure, scalable, and commercially viable architectures.
• Define reference architectures and design standards for LLM integrations, RAG pipelines, agentic workflows, MCP-based integrations, and enterprise data platforms.
• Partner with pre-sales and business development teams to prepare RFP responses, technical proposals, solution presentations, and architecture documents.
• Lead client discovery sessions and technical presentations, communicating architectural decisions and trade-offs to technical and executive stakeholders.
• Conduct architecture reviews and technical assessments to ensure scalability

Position

Solution Architect/Technical Architect

Experience

·       12 - 16+ years of overall IT experience

·       Significant hands-on experience working as a Solution/Technical Architect

Education

·       B.Tech / M.Tech / MCA / MBA or equivalent

Certifications

·       TOGAF® certification (Level 1/2) preferred to ensure alignment with enterprise architecture standards

·       Microsoft Certified: Azure Solutions Architect Expert (AZ-305) and other supporting certifications such as AZ-104, AZ-400, or AZ-500 preferred.

Key Responsibilities

·       Define and evolve the target architecture for .NET-based distributed platform.

·       Architect highly configurable solutions on Azure with strong focus on scalability, tenant isolation, resilience, maintainability, and speed of delivery.

·       Lead solution design across ASP.NET Core services, REST APIs, event-driven workflows, background processing, integration patterns, and shared platform capabilities.

·       Drive adoption of modern .NET and cloud-native patterns including microservices, domain-driven design, event-driven architecture, API-first design, and secure service-to-service communication.

·       Partner with engineering teams on real implementation decisions, review critical designs and code paths, and provide hands-on guidance for performance, operability, and production readiness.

·       Architect Azure-native deployment patterns using AKS, containers, API Management, Service Bus/Event Grid or equivalent messaging, Key Vault, managed observability, and CI/CD automation.

·       Work with data and platform teams on PostgreSQL-backed service design, data access patterns, caching strategies, and database performance for high-volume transactional workloads.

·       Define non-functional requirements and architecture guardrails around performance, scalability, availability, recoverability, security, compliance, and cost efficiency.

·       Embed DevSecOps and observability into platform design through telemetry, tracing, alerting, diagnostics, secrets management, and release governance.

·       Evaluate emerging technologies, AI-assisted engineering enablers, and modernization options pragmatically, with clear build-vs-buy and risk-reward trade-offs.

·       Mentor senior engineers and technical leads, contribute to architectural governance, and create reusable patterns, reference implementations, and standards across teams.

·       Bachelor’s or master’s degree in computer science, Engineering, or a related field.

·       12–16 years of experience in software engineering, solution architecture, or platform engineering, with significant experience in Microsoft technology stacks.

Essential Qualification and Skills

·       Strong hands-on expertise in C#, .NET / .NET Core / .NET 8, ASP.NET Core, Web APIs, background services, and enterprise application design.

·       Deep experience in architecting distributed systems using microservices, asynchronous messaging, event-driven design, and API-led integration patterns.

·       Strong Azure architecture experience, preferably across AKS, App Services, Functions, API Management, Key Vault, Service Bus, Event Grid, Storage, monitoring, and identity integration patterns.

·       Experience designing and supporting platforms, configurable product architectures, and integration-heavy enterprise solutions.

·       Strong understanding of relational databases and performance engineering, especially SQL Server and/or PostgreSQL, including schema design, indexing, query tuning, and transaction handling.

·       Solid grasp of non-functional architecture including performance, scalability, availability, fault isolation, observability, and disaster recovery.

·       Strong understanding of application and platform security including authentication, authorization, secrets management, encryption, secure coding, and compliance-oriented design.

·       Experience with containers, Kubernetes, CI/CD, infrastructure automation, and modern DevSecOps practices.

·       Ability to make sound architecture decisions with a balance of pragmatism, delivery speed, engineering quality, and long-term maintainability.

·       Strong communication and stakeholder management skills across product, engineering, architecture, operations, security, and client-facing teams.

Skills & Competencies

·       Experience in insurance, Insurtech, BFSI, or other regulated, transaction-heavy domains.

·       Exposure to policy administration, billing, accounting, claims, workflow orchestration, or reporting platforms within the insurance value chain.

·       Experience with architecture frameworks and modelling approaches such as TOGAF, domain-driven design, UML, C4, or equivalent practical architecture methods.

·       Familiarity with mixed technology landscapes involving .NET, Java/Spring Boot, enterprise workflow tools, and integration ecosystems.

·       Experience with observability and reliability tooling such as Datadog, Dynatrace, Application Insights, Open Telemetry, Grafana, or similar.

·       Working knowledge of Angular, React, or modern web application architecture patterns.

·       Exposure to AI-enabled engineering, intelligent automation, or embedding AI capabilities into enterprise platforms.

·       Leadership experience across globally distributed or virtual teams.