Director, Software Engineer

Morgan Stanley•Alpharetta, GA

6d•Hybrid

About The Position

Morgan Stanley Services Group, Inc. is seeking a Director, Software Engineer in Alpharetta, Georgia to integrate Large Language Models (LLMs) into existing applications to enhance user experience. Design, implement, and optimize LLM-based solutions ensuring production-grade quality. Develop APIs and middleware to facilitate seamless communication between LLMs and existing systems. Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to define requirements and deliver solutions. Monitor, analyze, and fine-tune LLM performance using metrics and user feedback. Implement security best practices and data privacy policies for LLM interactions. Stay updated with advancements in AI, NLP, and machine learning to continuously improve integration strategies. Integrate GenAI capabilities into enterprise applications, including designing end-to-end GenAI pipelines and autonomous or semi-autonomous agent workflows. Create structured prompts, templates, and reusable prompt-engineering frameworks for diverse business use cases. Design and implement GenAI agents capable of reasoning, planning, and executing actions across internal APIs, enterprise tools, and third-party services. Develop and maintain tool registries enabling GenAI agents to securely interact with enterprise systems and data sources. Implement metrics, observability, tracing, and structured logging for GenAI workloads. Build rapid Proofs of Concept (POCs) to validate GenAI ideas, measure ROI, and scale successful prototypes into production-ready systems. Participate in Agile ceremonies, including sprint planning, retrospectives, and continuous improvement initiatives. Conduct code reviews, design reviews, and prompt-optimization sessions to maintain engineering quality.

Requirements

Bachelor’s in Computer Engineering, Computer Science, or a related field of study.
Five (5) years of experience in the position offered or as a Full Stack Developer, Software Engineer, AI Engineer, or a related role.
Five (5) years of experience with Full stack development skills in Python, Java and JavaScript.
Five (5) years of experience with Working with different tools of Adobe Marketing cloud including Adobe Experience Manager, Target and Campaign.
Five (5) years of experience with RESTful API development and integration.
Five (5) years of experience with GraphQL API to serve dynamic request on data.
Five (5) years of experience with Backend development experience with Node.js and Nest.js.
Five (5) years of experience with Frontend development experience with Angular and React.
Five (5) years of experience with DevOps tools and practices for deployment and monitoring.
Five (5) years of experience with Implementing Continuous Integration and Continuous Deployment (CICD) pipelines using Jenkins, Bamboo, and Docker.
Five (5) years of experience with Atlassian’s toolset, including JIRA, Confluence, Box, BitBucket, Git repository, SVN, and SourceTree.
Two (2) years of experience with AWS Lambda.
Two (2) years of experience with AWS Gateway API.
Two (2) years of experience with AWS SDK and AWS CDK.
Two (2) years of experience with LLM APIs including OpenAI, Azure OpenAI, and Hugging Face.
Two (2) years of experience with Prompt engineering frameworks, GenAI agent frameworks including LangChain, LlamaIndex, and Semantic Kernel.
Two (2) years of experience with Performing model fine-tuning, embeddings, and secure tool registries.
Two (2) years of experience with Utilizing observability tools including TruLens, and W&B.
Two (2) years of experience with OAuth2.
Two (2) years of experience with SAML authentication.
Two (2) years of experience with API gateways.
Two (2) years of experience with Kubernetes Helm.
Two (2) years of experience with Terraform.
Two (2) years of experience with Prometheus.
Two (2) years of experience with Grafana, and enterprise.
Two (2) years of experience with AI safety and compliance practices.

Responsibilities

Integrate Large Language Models (LLMs) into existing applications to enhance user experience.
Design, implement, and optimize LLM-based solutions ensuring production-grade quality.
Develop APIs and middleware to facilitate seamless communication between LLMs and existing systems.
Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to define requirements and deliver solutions.
Monitor, analyze, and fine-tune LLM performance using metrics and user feedback.
Implement security best practices and data privacy policies for LLM interactions.
Stay updated with advancements in AI, NLP, and machine learning to continuously improve integration strategies.
Integrate GenAI capabilities into enterprise applications, including designing end-to-end GenAI pipelines and autonomous or semi-autonomous agent workflows.
Create structured prompts, templates, and reusable prompt-engineering frameworks for diverse business use cases.
Design and implement GenAI agents capable of reasoning, planning, and executing actions across internal APIs, enterprise tools, and third-party services.
Develop and maintain tool registries enabling GenAI agents to securely interact with enterprise systems and data sources.
Implement metrics, observability, tracing, and structured logging for GenAI workloads.
Build rapid Proofs of Concept (POCs) to validate GenAI ideas, measure ROI, and scale successful prototypes into production-ready systems.
Participate in Agile ceremonies, including sprint planning, retrospectives, and continuous improvement initiatives.
Conduct code reviews, design reviews, and prompt-optimization sessions to maintain engineering quality.