Solution Architect

Luxoft; Hyderabad; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Luxoft is seeking a seasoned Solution Architect to design and govern scalable software solutions for Capital Markets analytics platforms. The role focuses on traditional client-server and AWS cloud architectures, AI infrastructure, and governance to align with security standards and responsible AI policies.

The candidate will drive end-to-end architecture, define patterns and reusable frameworks, and ensure high availability, cost optimization, and performance.

Qualifications

• 8-12+ years in software engineering and architecture roles.
• Proven experience designing large-scale distributed systems.
• Knowledge of .NET and/or Python.
• Strong knowledge of Microservices and API management and integrations.
• Experience with AWS compute, containers, networking and data services (EC2, Lambda, S3, RDS).
• Hands-on with AI/ML stacks and observability tools.

Responsibilities

• Architecture & Solution Design across capital markets analytics platforms.
• Translate business requirements into scalable, secure technical solutions.
• Define architecture patterns, standards, and reusable frameworks.
• Ensure interoperability across systems, data layers, and AI services.
• Architect cloud-native and hybrid solutions on AWS and define migration strategies.
• Implement IaC and automation for governance and reliability.
• Guide AI governance, observability, and agent control in enterprise platforms.
• Mentor architects and align cross-functional teams.

Skills

Core Architecture

Years of Experience

Distributed Systems

Python / .NET

Microservices

API Management

AWS Technologies

AI/ML & LLMs

Architectural Frameworks

Stakeholder Communication

Tools

Amazon EC2

AWS Lambda

ECS / EKS

VPC & Networking

API Gateway

CloudFormation / CDK / Terraform

CodePipeline / CodeBuild / CodeDeploy

OpenTelemetry / Langfuse / Prometheus

Job description

Project description

We are seeking a highly experienced Solution Architect to design, guide, and govern scalable software solutions across the Capital Markets analytics platforms.This role requires strong expertise in traditional client-server architecture, AWS cloud technologies, AI infrastructure, and advanced AI governance practices, ensuring solutions align with business strategy, security standards, and responsible AI policies.

Responsibilities

• Architecture & Solution Design
• Design end-to-end solution architectures spanning:o Component-level services (microservices, APIs)o Domain platforms
• Define architecture patterns, standards, and reusable frameworks
• Translate business requirements into scalable and secure technical solutions
• Ensure interoperability across systems, data layers, AI services, and platformsCloud Architecture (AWS)
• Architect and optimize cloud-native and hybrid solutions using AWS services
• Define cloud migration strategies and modernization approaches
• Ensure high availability, resiliency, cost optimization, and performance
• Implement Infrastructure-as-Code and automation best practicesAI, Data & Intelligent Systems Architecture
• Design AI/ML infrastructure, pipelines, and enterprise integration patterns
• Architect solutions incorporating LLMs, generative AI, and intelligent agents
• Guide adoption of AI technologies within enterprise platforms and products
• Establish patterns for:o RAG (Retrieval-Augmented Generation)o Feature stores and data pipelineso Model deployment, versioning, and scalingAI Governance, Observability & Control
• Define and implement enterprise AI governance frameworks covering:o Responsible AI usage (fairness, bias mitigation, explainability)o Data privacy, lineage, and complianceo AI risk classification and policy enforcement
• Establish AI observability and monitoring capabilities, including:o End-to-end tracing of AI/ML and LLM flows using tools such as OpenTelemetryo Monitoring of prompts, responses, latency, and model behavior using platforms like Langfuse or equivalento Metrics for model performance, drift, hallucination rates, and usage patterns
• Design and enforce agent governance and control mechanisms, including:o Monitoring and auditing of autonomous and semi-autonomous AI agentso Guardrails for agent behavior, tool usage, and decision boundarieso Human-in-the-loop (HITL) workflows and escalation patternso Policy-based control over agent actions and integrations
• Implement AI lifecycle governance, including:o Model validation, approval workflows, and audit trailso Continuous evaluation and feedback loopso Secure model and prompt managementCross-Disciplinary Architecture Leadership
• Act as a strategic liaison across Semantic, Data, and ML architecture domains
• Facilitate alignment between knowledge graphs, ontologies, data platforms, and ML systems
• Provide architectural guidance to specialized architects, ensuring cohesive enterprise integration
• Bridge gaps between business semantics, data engineering, and machine learning pipelinesSecurity, Compliance & Governance
• Ensure architectures meet enterprise security standards (e.g., Zero Trust)
• Define policies for data governance, access control, and auditability
• Align AI and cloud solutions with regulatory and compliance frameworksCollaboration & Leadership
• Work with engineering, product, data, and AI teams to align solutions
• Mentor architects and senior engineers
• Act as a trusted advisor to leadership and stakeholders

SKILLS

Must have

• Core Architecture
• 8-12+ years in software engineering and architecture roles
• Proven experience designing large-scale distributed systems
• Knowledge of .NET and/or Python
• Strong knowledge of:o Microservices and event-driven architectureso API management and integrationsAWS TechnologiesCompute & Containers
• Amazon EC2, AWS Lambda
• Amazon ECS / EKS (Kubernetes)Networking & Integration
• Amazon VPC, Route 53, API Gateway
• AWS App Mesh, EventBridge, SNS, SQSData & Storage
• Amazon S3, EBS, Glacier
• Amazon RDS, Aurora, DynamoDB, RedshiftDevOps & Automation
• AWS CloudFormation / CDK / Terraform
• AWS CodePipeline, CodeBuild, CodeDeployObservability
• Amazon CloudWatch, AWS X-RaySecurity
• AWS IAM, Cognito, KMS, Secrets Manager
• AWS Organizations and Control TowerAI/ML, LLM & Observability Expertise
• Experience with AWS AI/ML stack:o Amazon SageMakero Amazon Bedrock (LLMs & foundation models)o AWS Glue, Lake Formation
• Hands-on experience with:o LLM-based architectures and agent-based systemso AI observability tools (e.g., OpenTelemetry, Langfuse, Prometheus/Grafana)o Prompt lifecycle management and evaluation pipelines
• Strong understanding of:o AI governance frameworks and enterprise AI controlso Agent orchestration, monitoring, and guardrailso Data lineage, quality, and complianceArchitecture Frameworks & Practices
• TOGAF or equivalent enterprise architecture frameworks
• Domain-driven design (DDD)
• Cloud-native and serverless patterns
• Experience integrating data, semantic, and ML architecturesSoft Skills
• Strong communication and stakeholder management
• Strategic thinking with hands‑on technical depth
• Ability to influence senior leadership and cross‑functional teams
• Mentorship and leadership capabilities

Nice to have

AWS Certified Solutions Architect - ProfessionalAWS Specialty Certifications (Machine Learning, Security)Experience implementing AI governance frameworksBackground in regulated industriesExposure to multi-cloud or hybrid environments