Senior Associate Software Engineer

The candidate will collaborate with product managers, UX/UI designers, engineers, data teams, QA, cybersecurity, and DevOps teams to deliver secure, reliable, and maintainable solutions.

Roles and Responsibilities

Develop, test, deploy, and maintain scalable software applications.

Build front-end applications using React, Vite, TypeScript, and modern UI-development practices.

Develop back-end applications, RESTful APIs, integration services, and data-access components using Python and FastAPI.

Build responsive, accessible user interfaces and reusable UI components aligned with enterprise UX standards.

Translate business requirements into secure, maintainable, production-ready solutions.

Contribute to software-design discussions and technical decisions.

Develop cloud-native applications using APIs, microservices, serverless services, containers, and event-driven patterns.

Integrate applications with enterprise platforms, identity services, databases, cloud services, and third-party systems.

Develop AI-enabled applications using Generative AI, LLMs, RAG, and related technologies where appropriate.

Collaborate with data scientists and ML engineers to integrate predictive models and AI capabilities.

Support model-serving APIs and MLOps processes for deployment and monitoring.

Develop unit, integration, end-to-end, regression, and automated acceptance tests.

Participate in peer code reviews and follow coding, security, and quality standards.

Apply secure software-development practices throughout the development lifecycle.

Use tools such as Veracode, Snyk, SonarQube, or equivalent platforms and remediate identified findings.

Contribute to CI/CD pipelines and automate build, testing, security validation, and deployment.

Troubleshoot application defects, production incidents, integration issues, and performance bottlenecks.

Implement logging, monitoring, alerting, and operational dashboards.

Maintain technical documentation, including solution designs, API specifications, deployment guides, and support procedures.

Collaborate with product, UX/UI, QA, data engineering, cybersecurity, architecture, and DevOps teams.

Participate in Agile ceremonies, estimation, and release planning.

Stay current with emerging software, cloud, security, UI, and AI technologies.

Participate in production support activities, including occasional off-hours support.

Basic Qualifications and Experience

Master’s or Bachelor’s degree and 5–9 years of experience in Computer Science, Information Technology, Software Engineering, Engineering, or a related field.

Must-Have Skills

Strong foundation in software design, object-oriented programming, design patterns, RESTful APIs, microservices, cloud-native applications, and containerization.

Strong hands-on experience with full-stack software development.

Strong proficiency in Python, TypeScript or JavaScript, HTML5, CSS3, and SQL.

Proficiency in FastAPI, including API design, validation, dependency injection, authentication, exception handling, testing, and deployment.

Hands-on experience developing modern web applications using React and Vite.

Experience with component-based architecture, state management, routing, reusable components, responsive design, and performance optimization.

Experience integrating applications with RESTful or GraphQL APIs, databases, enterprise platforms, and third-party services.

Understanding of web accessibility standards, including WCAG.

Experience with cloud-based application development, with AWS preferred.

Familiarity with AWS services such as Lambda, ECS, EKS, API Gateway, S3, RDS, DynamoDB, CloudWatch, and EventBridge.

Experience with Git, CI/CD, automated testing, code-quality controls, and production deployment.

Experience with Docker and containerized application development.

Understanding of authentication, authorization, RBAC, secrets management, secure APIs, and OWASP Top 10.

Experience with application-security or code-quality tools such as Veracode, Snyk, SonarQube, Checkmarx, Fortify, or equivalent platforms.

Experience analyzing and remediating code-quality, dependency, and security findings.

Understanding of Generative AI concepts, including LLMs, RAG, prompt engineering, embeddings, and AI-assisted development.

Experience using tools such as GitHub Copilot, OpenAI Codex, Cursor, or equivalent approved platforms.

Strong analytical, debugging, troubleshooting, and problem-solving skills.

Experience delivering software using Agile methodologies.

Good-to-Have Skills

Experience with UI component libraries such as Material UI, Ant Design, or Fluent UI.

Experience with Kubernetes and container orchestration.

Experience with AWS-native serverless and cloud-native architectures.

Experience with Infrastructure as Code using Terraform, AWS CDK, CloudFormation, or equivalent tools.

Experience with monitoring tools such as CloudWatch, Prometheus, Grafana, Splunk, Datadog, or OpenTelemetry.

Experience with relational and NoSQL databases.

Experience with message queues, asynchronous processing, and event-driven technologies.

Familiarity with DevSecOps, software composition analysis, penetration testing, and container-security scanning.

Experience with machine learning model integration, model-serving APIs, or MLOps platforms.

Experience developing GenAI applications using LangChain, LangGraph, LlamaIndex, Semantic Kernel, Amazon Bedrock, or equivalent technologies.

Experience with vector databases and semantic search.

Experience collaborating with UX/UI designers.

Experience in biotechnology, pharmaceutical, life sciences, manufacturing, or another regulated industry.

Preferred Certifications

AWS Certified Developer, Solutions Architect, or another relevant cloud certification.

Relevant software-development, DevOps, Kubernetes, application-security, AI, or machine-learning certification.

Scaled Agile Framework certification.

Soft Skills

Excellent analytical and troubleshooting skills.

Strong verbal and written communication skills.

Ability to work effectively with global and virtual teams.

High degree of initiative, ownership, and self-motivation.

Ability to manage multiple priorities and meet delivery commitments.

Strong teamwork, collaboration, and presentation skills.

Ability to explain technical concepts to technical and non-technical stakeholders.

Strong attention to software quality, security, reliability, and continuous learning.

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