Job DescriptionJob Summary:This position works with cutting edge technology, deliver high quality solutions across various industries and collaborate with teams on engagements that range in size and scope. This position receives continuous career development opportunities, given the size and potential of client engagements. This role performs hands-on delivery of enterprise AI solutions including Generative AI applications, AI agents, retrieval-augmented generation (RAG) architectures, multimodal systems, cloud-native AI platforms, and traditional AI/ML solutions
Job Duties:- Designs, and implements best in class solutions that include AI and cognitive services, ML models, data ingestion strategies, semantic layers and models, visualizations, streaming processes, API integrations, and automation (RPA) solutions for end-to-end data analytics solutions on primarily, but not limited to, cloud analytics platforms such as Azure and AWS
- Leverage multiple Large Language Models (LLM) to enhance natural language processing capabilities and develop advanced AI applications.
- Designs and implements solutions incorporating retrieval-augmented generation (RAG) architectures and multimodal embeddings to enhance AI-driven insights by combining text, images, and structured data sources
- Listens to client needs to align solutions with business requirements and delivery schedules
- Creates written functional and technical designs
- Participates in project status and stand meetings, and assists with providing aggregated project status for project and program managers
- Assists with SLA compliance of solutions, and performs performance tuning and optimization efforts of end-to-end solutions
- Writes code using multiple languages and correctly applies frameworks, architectural patterns, and software development principles
- Delivers high-performance, scalable, repeatable, and secure deliverables with broad impact (high throughput and low latency)
- Assists with implementation of governance programs and best practices
- Performs the cleaning and transforming of data from source systems into analytics models
- Implements models to support data visualizations and integrations
- Implements MLOps, LLMOps, AgentOps, DevOps, and DataOps practices including model evaluation, prompt versioning, continuous deployment, monitoring, and lifecycle management of AI solutions
- Writes custom integration logic in applicable programming languages
- Assists project managers with work breakdown structure creation, project estimation, resource staffing, workload planning and adjustments throughout the project lifecycle
- Assists clients with licensing, security, and cost estimation of solutions
- Performs code reviews to ensure adherence to standards
- Works directly with clients and team members to establish secure data analytics platforms and infrastructure
- Contributes to successful deployments of developed solutions and integration of DevOps, AIOps, and MLOps tools
- Maintains a broad and current understanding of data analytics and business intelligence strategies, cloud platforms, methodologies, and tools
- Builds client relationships during project execution, effectively becoming a trusted advisor of the client
- Participates in support activities for existing software solutions
- Other duties as assigned
Supervisory Responsibilities:- Mentors and advises the day-to-day workload of Associates on assigned engagements to ensure that timelines and deliverables are met, and reviews work product
Qualifications, Knowledge, Skills, and Abilities:Education:- Bachelor's degree, required; focus in Information Systems, Data Science or Computer Science, preferred
Experience:- Five (5) or more years of experience within Artificial Intelligence, Data Analytics, Business Intelligence, Machine Learning, Application Development, required
- One (1) or more years of experience technically leading development projects, preferred
- One (1) or more years of consulting experience or implementation of cloud-based data analytics and AI solutions, preferred
License/Certifications:Software:- Strong experience with AI/ML model lifecycle, required
- Experience with enterprise AI platforms such as Azure AI Foundry, Azure OpenAI Service, AWS Bedrock, AWS SageMaker, or Google Vertex AI, required
- Strong experience with Large Language Models (LLM), prompt engineering, retrieval-augmented generation (RAG), vector databases, and AI orchestration frameworks, required
- Strong SQL skills including Data Definition Language (DDL), Data Manipulation Language (DML), views, functions, stored procedures, or performance tuning, required
- Experience with one (1) or more of the following computer languages, preferred:
- Hands on delivery experience of end-to-end cloud data analytics solutions within Azure or AWS, preferred
- Experience with Data Warehousing, Data Modeling, Semantic Model Definition or Star Schema Construction, preferred
- Experience with tabular modeling within Power BI or Azure Analysis Services, preferred
- Experience with Git, DevOps, and MLOps deployment technologies, preferred
- Experience with Linux, preferred
- Experience with one (1) or more of the following, preferred:
- AI Algorithms/Machine Learning
- Computer Vision based AI technologies
Language:Other Knowledge, Skills & Abilities:- Ability to work with a high degree of professionalism and autonomy
- Excellent verbal and written communication skills
- Solid organizational skills, especially the ability to meet project deadlines with a focus on details
- Ability to successfully multi-task while working independently or within a group environment
- Ability to work in a deadline-driven environment, and handle multiple projects simultaneously
- Ability to interact effectively with people at all organizational levels of the Firm
- Ability to effectively interact with a team of professionals and delegating work assignments, as needed
- Ability to build and maintain strong relationships with internal and client personnel
Keywords: Data Analytics, Business Intelligence, BI, Solution Architect, Data Architect, Synapse, IoT, Machine Learning, PyTorch, TensorFlow, Data Lake, Stream, Cube, Microsoft, SQL Server, Tableau, .Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL, LLM, Bedrock, SageMaker, Azure Foundry, Google Vertex, RAG
