Specialist Software Engineer

Role Description

We are seeking an experienced Specialist Software Engineer to lead the design, development, deployment, and operation of scalable enterprise software solutions. This role combines full-stack development, cloud engineering, DevOps, application security, system reliability, and AI-enabled solution development.

The ideal candidate has strong hands-on experience with React, Vite, FastAPI, Python, TypeScript or JavaScript, APIs, microservices, AWS, containerization, CI/CD, DevSecOps, and production operations. The role will provide technical leadership, establish engineering standards, mentor developers, and collaborate with product, design, data, quality, cybersecurity, and platform teams.

Roles and Responsibilities

• Lead the design, development, testing, deployment, and support of complex enterprise software solutions.

• Own software initiatives from requirements and architecture through production deployment and operational support.

• Manage technical scope, risks, dependencies, estimates, and delivery timelines.

• Translate business requirements into scalable, secure, resilient, and maintainable solutions.

• Develop responsive front-end applications using React, Vite, and TypeScript.

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

• Build cloud-native solutions using microservices, serverless technologies, containers, APIs, and event-driven patterns.

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

• Develop AI-enabled applications using machine learning, Generative AI, LLMs, and Retrieval-Augmented Generation whereappropriate.

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

• Establish reusable design patterns, coding standards, engineering practices, and technical documentation.

• Lead architecture, design, and code reviews to ensure quality, security, performance, and maintainability.

• Apply secure software-development practices and integrate security testing into the software-development lifecycle.

• Use tools such as Veracode, Snyk, SonarQube, Checkmarx, Fortify, or equivalent platforms to identify and remediate security and code-quality findings.

• Implement unit, integration, regression, performance, and automated acceptance testing.

• Develop CI/CD pipelines, automated deployments, infrastructure automation, and security quality gates.

• Implement application monitoring, logging, tracing, alerting, and operational dashboards.

• Improve application availability, scalability, reliability, performance, and disaster-recovery readiness.

• Lead troubleshooting, root-cause analysis, incident response, and remediation of complex production issues.

• Provide technical guidance, coaching, and mentorship to junior and mid-level engineers.

• Collaborate with product managers, designers, QA, architects, DevOps, cybersecurity, data teams, and business stakeholders.

• Participate in Agile planning, estimation, roadmap development, and delivery activities.

• Evaluate emerging technologies based on business value, security, scalability, maintainability, and cost.

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

Basic Qualifications and Experience

• Bachelor’s or Master’s degree in Engineering, Computer Science, Information Technology, Business, or a related field, with 8–12 years of relevant professional experience.

Must-Have Skills

• Strong foundation in software architecture, object-oriented design, design patterns, and software-engineering best practices.

• Advanced hands-on experience with full-stack software development.

• Strong proficiency in Python, TypeScript or JavaScript, and SQL.

• Strong proficiency in FastAPI, including API design, validation, asynchronous processing, authentication, testing, and production deployment.

• Strong experience developing modern web applications using React and Vite.

• Experience with front-end state management, routing, reusable components, responsive design, accessibility, and performance optimization.

• Experience designing RESTful APIs, microservices, asynchronous integrations, and event-driven solutions.

• Strong cloud-native development experience, with AWS preferred.

• Experience with relevant AWS services such as Lambda, ECS, EKS, API Gateway, S3, RDS, DynamoDB, CloudWatch, EventBridge, and Step Functions.

• Experience with Docker, Kubernetes, Git, CI/CD, automated testing, and production deployment.

• Strong knowledge of secure software development, OWASP Top 10, authentication, authorization, RBAC, encryption, secrets management, and dependency security.

• Hands-on experience with application-security and code-quality tools such as Veracode, Snyk, SonarQube, Checkmarx, Fortify, or equivalent platforms.

• Experience integrating code, dependency, container, and security scanning into CI/CD pipelines.

• Experience assessing and remediating security vulnerabilities and code-quality findings.

• Experience designing highly available, scalable, fault-tolerant, and maintainable systems.

• Experience with monitoring, logging, tracing, alerting, and production troubleshooting.

• Experience leading technical designs, code reviews, and complex software deliveries.

• Demonstrated ability to mentor engineers and establish reusable engineering standards.

• Strong Agile delivery, analytical, debugging, and problem-solving skills.

AI and Machine Learning Capabilities

• Experience incorporating AI or machine learning capabilities into enterprise applications.

• Understanding of model integration, model serving, APIs, and production deployment patterns.

• Familiarity with frameworks such as Scikit-learn, TensorFlow, PyTorch, or equivalent technologies.

• Experience developing Generative AI applications using LLMs, prompt engineering, embeddings, vector search, or RAG.

• Understanding of AI security, privacy, evaluation, monitoring, governance, and responsible AI.

Good-to-Have Skills

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

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

• Experience with observability tools such as CloudWatch, Prometheus, Grafana, Splunk, or OpenTelemetry.

• Experience with relational and NoSQL databases and performance optimization.

• Experience with Kafka, Amazon Kinesis, Amazon SQS, or other asynchronous and streaming technologies.

• Experience with MLOps platforms such as MLflow, SageMaker, Kubeflow, or Airflow.

• Experience with Apache Spark, PySpark, Databricks, or other data-processing technologies.

• Experience with threat modeling, penetration testing, software composition analysis, and software supply-chain security.

• Experience implementing DevSecOps practices across web, API, cloud, and container environments.

• Experience with disaster recovery, business continuity, and operational-readiness planning.

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

Preferred Certifications

• AWS Certified Developer, Solutions Architect, or DevOps Engineer certification.

• Relevant cloud, Kubernetes, software architecture, security, or DevSecOps certification.

• Relevant AI, machine learning, or Generative AI certification.

• Scaled Agile Framework certification.

Soft Skills

• Excellent analytical, troubleshooting, and decision-making skills.

• Strong verbal, written, presentation, and stakeholder-communication skills.

• Ability to work effectively with global and virtual teams.

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

• Ability to manage multiple priorities, dependencies, and delivery risks.

• Strong leadership, mentoring, collaboration, and influencing skills.

• Commitment to quality, security, reliability, and operational excellence.