Brillio

Architect

• Design scalable, fault tolerant, and high availability backend systems using Node.js
• Define microservices, event driven, and API first architectures
• Create low level and high level design documents (LLD/HLD)
• Establish coding standards, best practices, and architectural guidelines
• Evaluate and recommend frameworks, libraries, and tools
• Lead complex backend development initiatives using Node.js (Express/NestJS/Fastify)
• Review code for performance, security, maintainability, and scalability
• Mentor senior and junior developers; conduct design and code reviews
• Collaborate with frontend, DevOps, QA, and product teams
• Optimize application performance, memory usage, and async workflows
• Implement authentication, authorization, and data security best practices
• Design logging, monitoring, alerting, and observability solutions
• Ensure compliance with security standards and data protection policies
• Design cloud native solutions on AWS / Azure / GCP
• Work closely with DevOps on CI/CD pipelines, containerization, and deployments
• Guide infrastructure design using Docker, Kubernetes, and IaC
• Ensure system resilience and disaster recovery strategies

Node JS Architect

Data Engineer

Data Engineer, Databricks

Network Engineer

• Design, build, and own Azure infrastructure using Terraform as the primary IaC tool.
• Create reusable Terraform modules from scratch, not just consume existing templates.
• Integrate Terraform with Azure DevOps YAML pipelines for controlled CI/CD deployments.
• Perform root‑cause analysis for failed Terraform plans/applies and configuration drift.
• Refactor manually created Azure resources into fully Terraform‑managed infrastructure.
• Act as the primary Network Engineering SME for Azure and hybrid environments.
• Design and troubleshoot Azure VNETs, subnets, peering, and hub‑and‑spoke architectures.
• Demonstrate strong understanding of networking fundamentals, including TCP/IP and routing vs switching.

Azure Network Engineer

Software Engineer

• Analyze, triage, and remediate vulnerabilities identified via SAST, DAST, and software composition analysis tools such as SonarQube, Veracode, Snyk, and Checkmarx.
• Refactor insecure Java and Node.js codebases to mitigate vulnerabilities such as SQL Injection, XXE, XSS, CSRF, Deserialization, and Authentication flaws.
• Patch and upgrade vulnerable third-party dependencies using Maven/Gradle, and validate post-remediation effectiveness.
• Leverage Generative AI tools (e.g., AWS Bedrock) to build or enhance automation workflows for:
• Auto-remediation of common vulnerability patterns
• Code recommendations and patch generation
• AI-driven security analysis and triage assistance
• Automate vulnerability remediation and validation within CI/CD pipelines, improving security velocity and reducing manual effort.
• Strengthen security configurations in Spring Boot, REST APIs, Node.js services, and Tomcat-based deployments.
• Perform secure code reviews, provide remediation guidance, and promote secure coding best practices across development teams.
• Collaborate with InfoSec and DevOps teams to validate fixes, perform re-scans, and close vulnerability tickets.
• Stay current on security advisories, OWASP Top 10, CWE/SANS 25, and Java/Tomcat ecosystem updates.

Senior Node JS Developer

Machine Learning Engineer

• Architecting & Scaling Agentic AI Solutions • Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. • Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. • Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. • Hands-On Development & Optimization • Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. • Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. • Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. • Driving AI Innovation & Research • Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. • Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. • Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. • AI Strategy & Business Impact • Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. • Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. • Mentorship & Capability Building • Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. • Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents.

Senior AI/ML Engineer

Data Scientist

• Drive Agentic AI Strategy: Lead the architectural design of autonomous agents capable of L1/L2 incident triage, automated investigation, and proactive threat hunting.
• Cross-App Integration: Develop reusable integration patterns (Event-Driven, WebSockets, REST) to ensure the app is the "single pane of glass" for all connected applications.
• Conversational AI & STT: Design high-fidelity chatbot interfaces and real-time transcription services that allow operators to "talk to the data" and receive voice-activated summaries of active incidents.
• Data Science Leadership: Partner with Data Scientists to fine-tune LLMs, optimize Retrieval-Augmented Generation (RAG) pipelines, and ensure model outputs are grounded in enterprise-specific data.
• Scalability & Resilience: Ensure the architecture supports high-concurrency, low-latency operations.

Data Science Lead

• Problem Formulation (Business problem to Data Science Problem)
• OKR Validation against statistical measures
• Data Wrangling
• Data Storytelling & Insight Generation
• Problem Solving
• Excel VBA
• Data Curiosity
• Technical Decision Making (How many iterations to go for vs when to stop iterating)
• Communication & Articulation: Vocal & Written
• Business Acumen (Consume new domains quickly to learn through data)
• Design Thinking
• Data Literacy

• Assessment and discovery to define enterprise architecture strategy roadmap • Lead and design best-in-class, conceptual data models leading to implementable solution designs across technical ecosystem • Guide planning of data movement and integration patterns across our ecosystem, defining integration standards, reference architectures and tool utilization • Provide leadership and standard methodologies for using native-first connectors over third-party for integrating our various workflows, applications and data • Support master data solution architectures, system landscapes, governance workflows, and systems integration and implementation • Collaborating with business stakeholders and technical teams to understand data management requirements, data quality remediation and challenges, and identify opportunities for the design of a best of breed solution • Produce relevant solution design artifacts including but not limited to technical estimates, conceptual system designs, sequence diagrams, and data models • Act as an advisor for new and emerging technologies, patterns, and trends

Data Architect

Principal Data Scientist

Consultant

• Develop, test, and maintain SQL queries, stored procedures, and views to extract and transform data from multiple sources.
• Implement ETL workflows using SSIS and Denodo for data integration.
• Schedule and monitor jobs using Control-M to ensure timely data processing.
• Perform data profiling, source-to-target mapping, and data validation activities.
• Optimize SQL queries and troubleshoot performance issues.
• Support database operations on SQL Server and Oracle.
• Participate in unit testing and assist with data quality checks.

Senior Data Engineer

Project Manager

• Lead end-to-end delivery of Data Science, ML, and Engineering projects.
• Develop and manage project plans, timelines, resource allocations, and deliverables.
• Monitor project progress, manage risks, and drive resolution of roadblocks.
• Ensure high-quality, timely delivery across all phases—from requirements to deployment.
• Facilitate Scrum ceremonies including sprint planning, daily stand-ups, retros, and reviews.
• Maintain and optimize Jira boards, workflows, sprint metrics, and project visibility.
• Promote Agile best practices and continuous delivery improvements.
• Collaborate closely with Data Scientists, ML Engineers, Data Engineers, and Software teams.
• Understand data workflows, model development lifecycle, and engineering dependencies.
• Translate complex technical concepts into clear, actionable tasks for the team.
• Act as the primary point of contact for client interactions and status communication.
• Understand client expectations, gather requirements, and ensure alignment throughout delivery.
• Conduct regular status meetings, demos, and reviews with internal and external stakeholders.
• Build strong, trust-based relationships with business and technical partners.
• Prepare project documentation, dashboards, and executive status reports.
• Track KPIs, sprint velocity, program health, and delivery outcomes.
• Maintain transparent communication on progress, risks, and mitigation plans.

Senior Project Manager

Business Intelligence Developer

• Design, develop, and deploy SSIS packages for data extraction, transformation, and loading. • Implement incremental loads, error handling, logging, and performance tuning. • Integrate data from multiple sources such as SQL Server, Excel, flat files, and APIs. • Schedule and monitor ETL jobs using SQL Server Agent. • Ensure data quality and consistency across systems. • Develop and maintain SSRS reports including tabular, matrix, drill-down, and parameterized reports. • Create paginated reports for operational and financial reporting. • Configure report subscriptions and automated report delivery. • Implement report security and manage deployment across environments. • Optimize report performance and dataset queries. • Design and develop interactive dashboards and reports using Power BI. • Create complex DAX measures and calculated columns. • Develop optimized data models using star schema and best practices. • Implement Row-Level Security (RLS). • Publish and manage reports in Power BI Service. • Collaborate with business stakeholders to gather reporting requirements.

BI Specialist

• Develop Power BI reports and dashboards
• Build reporting models; manage data sources
• Transform data for business intelligence needs
• Interaction with clients for requirement gathering
• Work with various BI tools and systems

Node JS Architect

Data Engineer, Databricks

Azure Network Engineer

Senior Node JS Developer

Senior AI/ML Engineer

Data Science Lead

Data Scientist

Senior AI/ML Engineer

Data Architect

Principal Data Scientist

Consultant

Senior Data Engineer

Senior Project Manager

BI Specialist

BI Specialist – HLS