Solution Architect

Luxoft; Dadri; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

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

The candidate will architect end-to-end solutions, define patterns and standards, and drive modernization with a focus

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, API management, and AWS technologies.

Responsibilities

• Architect and govern scalable software solutions across Capital Markets analytics platforms.
• Lead end-to-end solution design spanning microservices, APIs, and domain platforms.
• Define architecture patterns, standards, and reusable frameworks.

Skills

Core Architecture

Distributed systems

.NET or Python

Microservices

AI governance

Stakeholder management

Tools

AWS

Kubernetes

Terraform

OpenTelemetry

Langfuse

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
  • Component-level services (microservices, APIs)
  • 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)
• Cloud 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 practices
• AI, 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
  • RAG (Retrieval-Augmented Generation)
  • Feature stores and data pipelines
  • Model deployment, versioning, and scaling
• AI Governance, Observability & Control
• Define and implement enterprise AI governance frameworks covering
  • Responsible AI usage (fairness, bias mitigation, explainability)
  • Data privacy, lineage, and compliance
  • AI risk classification and policy enforcement
• Establish AI observability and monitoring capabilities, including
  • End-to-end tracing of AI/ML and LLM flows using tools such as OpenTelemetry
  • Monitoring of prompts, responses, latency, and model behavior using platforms like Langfuse or equivalent
  • Metrics for model performance, drift, hallucination rates, and usage patterns
• Design and enforce agent governance and control mechanisms, including
  • Monitoring and auditing of autonomous and semi-autonomous AI agents
  • Guardrails for agent behavior, tool usage, and decision boundaries
  • Human-in-the-loop (HITL) workflows and escalation patterns
  • Policy-based control over agent actions and integrations
• Implement AI lifecycle governance, including
  • Model validation, approval workflows, and audit trail
  • Continuous evaluation and feedback loop
  • Secure model and prompt management
• Cross-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 pipelines
• Security, 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 frameworks
• Collaboration & 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
  • Microservices and event-driven architectures
  • API management and integrationsAWS TechnologiesCompute & Containers
• Amazon EC2, AWS Lambda
• Amazon ECS / EKS (Kubernetes)Networking & Integration
• 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
  • Amazon SageMaker
  • Amazon Bedrock (LLMs & foundation models)
  • AWS Glue, Lake Formation
• Hands-on experience with
  • LLM-based architectures and agent-based systems
  • AI observability tools (e.g., OpenTelemetry, Langfuse, Prometheus/Grafana)
  • Prompt lifecycle management and evaluation pipelines
• Strong understanding of
  • AI governance frameworks and enterprise AI control
  • Agent orchestration, monitoring, and guardrail
  • Data lineage, quality, and compliance
• TOGAF or equivalent enterprise architecture frameworks
• Domain-driven design (DDD)
• Cloud-native and serverless patterns
• Experience integrating data, semantic, and ML architectures
• 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 - Professional
• AWS Specialty Certifications (Machine Learning, Security)
• Experience implementing AI governance frameworks
• Background in regulated industries
• Exposure to multi-cloud or hybrid environments