Particle41

DevOps Engineer

• Work closely with software developers, system administrators, and other stakeholders to understand the requirements and objectives of projects.
• Collaborate on the design, implementation, and maintenance of continuous integration and delivery pipelines.
• Create and maintain comprehensive documentation for systems, processes, and configurations.
• Design, implement, and manage automation processes for software build, deployment, and configuration.
• Evaluate, select, and implement tools and technologies to enhance the efficiency of the development and deployment processes.
• Manage and maintain cloud-based infrastructure (AWS, Azure, GCP, and other cloud providers) to ensure scalability, reliability, and security.
• Implement infrastructure as code (IaC) using tools such as Terraform, Pulumi, and others.
• Establish and maintain CI/CD pipelines to automate the software delivery process, including build, test, and deployment phases.
• Develop and implement monitoring solutions to ensure the health and performance of systems and applications.
• Proactively identify and address issues related to system performance, reliability, and scalability.
• Implement and maintain security best practices in infrastructure and application deployment.
• Ensure compliance with regulatory requirements and company security policies.
• Provide support for development and operations teams, addressing issues related to build failures, deployment problems, and system outages.

AI Engineer

• Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring.
• Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals.
• Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks.
• Develop and integrate AI models into production systems (APIs, microservices, cloud deployments).
• Optimize models/solutions for performance, scalability, robustness and cost-efficiency.
• Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation.
• Document model design, experiments, data provenance and solution rationale.
• Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas.
• Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results.

Consultant

• Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines to process large volumes of data from diverse sources.
• Build and optimize data storage solutions, such as data lakes and data warehouses, to ensure efficient data retrieval and processing.
• Integrate structured and unstructured data from various internal and external systems to create a unified view for analysis.
• Ensure data accuracy, consistency, and completeness through rigorous validation, cleansing, and transformation processes.
• Maintain comprehensive documentation for data processes, tools, and systems while promoting best practices for efficient workflows.
• Collaborate with product managers, and other stakeholders to gather requirements and translate them into technical solutions.
• Participate in requirement analysis sessions to understand business needs and user requirements.
• Provide technical insights and recommendations during the requirements-gathering process.
• Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews.
• Work closely with Agile teams to deliver software solutions on time and within scope.
• Adapt to changing priorities and requirements in a fast-paced Agile environment.
• Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications.
• Write unit tests and validate the functionality of developed features and individual elements.
• Identify and resolve software defects, code smells, and performance bottlenecks.
• Stay updated with the latest technologies and trends in full-stack development.
• Propose innovative solutions to improve the performance, security, scalability, and maintainability of applications.
• Collaborate effectively with cross-functional teams, including testers, and product managers.

Data Consultant

Solutions Engineer

• Lead the design and architecture of cloud-native solutions using modern software stacks and AWS
• Define system architecture and design patterns to ensure scalability and reliability
• Evaluate and recommend technologies and frameworks to support business requirements
• Provide strategic guidance to align technical decisions with business goals
• Collaborate with stakeholders to define the technical roadmap and vision
• Drive innovation by researching emerging technologies and industry trends
• Mentor and coach team members to enhance their technical skills and expertise
• Conduct code reviews and provide constructive feedback to improve quality and maintainability
• Collaborate with cross-functional teams, including product managers, engineers, and QA
• Work closely with DevOps teams to ensure seamless integration and deployment processes
• Provide technical leadership and guidance on architectural decisions and implementations
• Identify and resolve technical challenges to ensure project success
• Drive continuous improvement initiatives to enhance development processes and methodologies
• Stay up to date with industry best practices and standards in software architecture

DevOps Engineer

AI Engineer

Data Consultant

Lead Software Solutions Architect