Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global management consulting and technology organization combines data, science, technology, and human ingenuity to develop innovative solutions that improve outcomes for patients, caregivers, consumers, and organizations worldwide. The organization works closely with clients to develop customized technology solutions and strategies that create measurable business value.
Key Responsibilities
- Oversee task planning and workload distribution across project teams.
- Serve as a trusted technical advisor to clients by translating complex AI and ML concepts into clear recommendations.
- Manage client expectations throughout the project lifecycle.
- Lead and mentor junior team members.
- Facilitate technical discussions with internal teams and client stakeholders to support effective decision-making and project success.
- Collaborate with technical architects to validate design and implementation approaches.
- Take ownership of architecture design and development for scalable and distributed software systems.
- Own technical execution while ensuring code quality, adherence to deadlines, and efficient resource allocation.
- Apply data-driven decision-making with a strong focus on achieving product goals.
- Design, develop, and deploy LLM-based pipelines using patterns such as Retrieval-Augmented Generation (RAG), agentic workflows, and Parameter-Efficient Fine-Tuning (PEFT), including LoRA and QLoRA.
- Manage the complete software development lifecycle, including requirements analysis, design, coding, testing, and deployment.
- Utilize AWS and Azure services covering identity and access management, monitoring, load balancing, autoscaling, databases, networking, storage, container registries, and related cloud infrastructure.
- Utilize Databricks capabilities, particularly Unity Catalog, to architect governance layers covering data through AI model outputs.
- Design, develop, and deploy prompt and response guardrails to support responsible AI requirements.
- Implement DevOps practices using technologies such as Docker and Kubernetes to support continuous integration and delivery.
- Develop automation and monitoring scripts to improve engineering efficiency and reliability.
- Collaborate with cross-functional teams, conduct code reviews, and provide guidance on software design and engineering best practices.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
- 6+ years of relevant professional experience.
- Strong coding skills with proficiency in Python and JavaScript.
- Experience with both stateless and stateful API frameworks, including FastAPI and Django.
- Strong proficiency with cloud platforms, particularly AWS, Databricks, and Azure.
- Experience with Infrastructure as Code, particularly Terraform and CloudFormation.
- Experience with front-end development technologies such as React JS, Next JS, and Tailwind CSS is preferred.
- Strong experience with LLM patterns including RAG, vector databases, hybrid search, agent development, agentic workflows, and prompt engineering.
- Strong experience working with LLM APIs such as OpenAI, Anthropic, and AWS Bedrock.
- Experience with AI and ML SDKs and frameworks such as LangChain and DSPy.
- Hands-on experience with DevOps technologies including Docker, Kubernetes, and AWS services such as Redshift, RDS, and S3.
- Hands-on experience with Databricks solutions, including Unity Catalog.
- Experience deploying production applications supporting thousands of users, including systems using Redis and vector search capabilities.
- Strong understanding of scalable application design principles.
- Experience implementing security best practices and complying with privacy and regulatory requirements.
- Good knowledge of software engineering practices, including Git, DevOps, and Agile or Scrum methodologies.
- Experience with Azure DevOps is preferred.
- Strong understanding of software development lifecycle practices and engineering standards.
- Experience working with Agile methodologies for continuous product development and delivery.
- Strong communication skills with the ability to convey complex technical concepts to diverse audiences.
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals globally.
- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
- To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
- No Liability: SpringCube is not liable for inaccuracies.
