We are seeking a highly skilled and motivated software Engineer with expertise in end-to-end solution development, deployment, and architecture across multiple domains.This role will focus on driving automation, scalability, and efficiency across our technical delivery ecosystem.
You'll work closely with solution architects and engineers to build assets and automations that can be integrated into repeatable client delivery work-streams.
Key Responsibilities
Solution Development & Implementation
- Design, develop, and deploy scalable, secure applications and AI-assisted features using cloud-native services such as AWS Lambda, EC2, S3, RDS, and related tools.
- Participate in the full application development lifecycle, including data processing, feature implementation, testing, deployment, and monitoring.
- Collaborate with senior engineers and architects to build production-ready, maintainable, and high-performance systems aligned with business objectives. Contribute to proof-of-concepts and prototypes involving new frameworks, algorithms, or AI-assisted features.
- Integrate basic AI/ML components or APIs into applications to enhance functionality and user experience.
- Implement and maintain CI/CD pipelines, version control, and automated testing for software and AI-assisted modules.
- Support integration of applications with enterprise systems, APIs, and data services across AWS.
- Follow established coding, testing, and documentation standards to ensure maintainability, security, and performance.
Collaboration & Continuous Improvement
- Work closely with architects, cloud engineers, and product teams to translate concepts into deployable solutions.
- Participate in architecture and code reviews to ensure high engineering standards. Support pre-sales or internal PoC efforts under senior guidance to demonstrate capabilities.
- Stay updated with emerging trends in AI/ML, GenAI, and MLOps, recommending improvements where relevant.
- Contribute to the internal AI Center of Excellence (CoE) by building reusable components, frameworks, and automation scripts.
Requirements
Qualifications & Skills
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 2+ years of hands-on experience in software or AI engineering, including application development, cloud-based architectures, and building CI/CD pipelines.
- Proficiency in Python and at least one additional programming language (e.g. Java, Go, C++, JavaScript, or Rust).
- Strong working knowledge of core AWS services used in software engineering, including Lambda, API Gateway, EC2, S3, RDS/DynamoDB, Step Functions, and related cloud-native tools. (Experience with Azure or GCP equivalents is a plus.).
- Working knowledge of data engineering concepts such as ETL pipelines, feature stores, or vector databases.
- Familiarity with LLMs and GenAI concepts (prompting, embeddings, RAG pipelines) is a plus.
- Strong grasp of software engineering best practices version control, testing, modular design, and cloud deployment.
- Excellent analytical, problem-solving, and communication skills.
- Preferred certifications: AWS Certified Machine Learning Specialty, AWS Solutions Architect Associate, or equivalent.
Signs You May Be a Great Fit
Impact: You want to play a pivotal role in shaping a rapidly growing, cloud-driven digital transformation venture studio.
Culture: You thrive in a collaborative, innovative environment that values creativity, ownership, and agility.
Growth: You seek continuous learning opportunities and mentorship from experienced peers.
Benefits: Competitive salary, wellness packages, and flexible work arrangements to support your lifestyle and goals.
