Were looking for a seasoned Software Development Engineer (SDE II) with deep expertise in Analytics and AI to join our high-impact engineering team.
In this role, youll collaborate closely with Design, Product, and cross-functional stakeholders to build innovative analytics and AI-driven solutions that help predict and prevent cyber breaches.
Core Responsibilities :
- AI & Analytics Development : Design, build, and deploy scalable AI-driven analytics solutions, leveraging advanced AI techniques, including Retrieval-Augmented Generation (RAG), AI agents, and foundational models.
- Architecture : Collaborate with cross-functional teams to architect scalable, secure, and performant AI-driven microservices.
- Cloud and AI Integration : Utilize cloud services (primarily AWS Bedrock, Lambda, EC2, S3, RDS) to develop efficient, robust, and scalable solutions.
- Model Evaluation : Implement and evaluate various AI models (e.g., OpenAI, Anthropic Claude, Amazon Titan), understanding trade-offs such as latency, cost, accuracy, and scalability.
- Code Quality : Ensure high-quality code through rigorous code reviews and continuous improvement processes.
- Problem Solving : Address complex technical challenges, identify root causes, and provide effective solutions.
- Cross-team Collaboration : Work closely with product managers, designers, and stakeholders to align technical solutions with business goals.
Essential Skills / Qualifications / Experience :
Bachelors or Master's degree in Computer Science, Engineering, or a related field.Minimum of 2 years of experience in software development roles, with expertise in Python, NodeJS, or Go.Strong hands-on experience with AI / ML, including Retrieval-Augmented Generation (RAG), AI Agents, and deploying these technologies into a production environment.Familiarity with AWS Bedrock and its AI model hosting ecosystem is highly advantageous.Experience with Typescript and API frameworks (Express) preferred.Good understanding of SQL and NoSQL databases.Demonstrable experience deploying scalable solutions in cloud environments (AWS preferred).Proficient in deploying containerized applications (Docker, Kubernetes, ECS).Knowledge of DevOps best practices and Infrastructure as Code (e.g., AWS CloudFormation) is beneficial.Exceptional leadership, communication, and mentoring skills.Proven capability to own features end-to-end in an agile, fast-paced environment.(ref : hirist.tech)