Clarity Innovations
Software Engineer (Senior RAG Integration Software Engineer) SWE3 (QC) TTO21-003
Clarity Innovations, Whitehurst, Maryland, United States,
Clarity Innovations connects human creativity with emerging technology to design, develop, and deploy software that enhances mission success. Our focus is redefining the Government’s relationship with technology by encouraging the use of DevSecOps and Agile methodologies, small-teams constructs, modern tech stacks, and automation. Our software improves the lives and work of our end users and enhances innovation. We fulfill our responsibility to our country by delivering mission-changing results that help shape a better and safer world.
Description:
We are seeking an experienced and innovative Senior RAG (Retrieval-Augmented Generation) Integration Software Engineer to lead our efforts in developing cutting-edge AI solutions. The ideal candidate will have a proven track record of designing, implementing, and optimizing RAG systems that seamlessly integrate information retrieval with advanced language generation models. This role requires a deep understanding of both traditional information retrieval techniques and state-of-the-art natural language processing. As a senior member of our team, you will be responsible for architecting robust RAG solutions, mentoring junior engineers, and driving technical decisions that shape the future of our AI-powered products. We are looking for a problem-solver who can adapt quickly to new challenges, communicate complex ideas effectively, and contribute to our culture of continuous learning and innovation.
Responsibilities:
Lead the design and implementation of scalable RAG systems that integrate seamlessly with our existing AI infrastructure.
Develop and optimize information retrieval algorithms to enhance the accuracy and relevance of generated content.
Implement and fine-tune large language models to work effectively within our RAG framework.
Create innovative solutions to combine retrieved information with generated text, ensuring coherent and contextually appropriate outputs.
Collaborate with cross-functional teams to integrate RAG capabilities into various products and services.
Mentor junior engineers and contribute to the technical growth of the team.
Stay abreast of the latest advancements in RAG, NLP, and related fields, and proactively incorporate new techniques into our systems.
Develop and maintain best practices for RAG system development, testing, and deployment.
Participate in code reviews, architectural discussions, and technical decision-making processes.
Interface with customers infrequently to gather product requirements and identify technical opportunities.
Skills Requirements:
Bachelor's degree in Computer Science, Artificial Intelligence, or a related field; advanced degree preferred.
12+ years of professional software engineering experience, with a strong focus on AI and NLP.
Extensive experience designing and implementing RAG systems or similar hybrid AI architectures.
Deep understanding of information retrieval techniques, including vector databases and embedding models.
Proficiency in working with and fine-tuning large language models.
Expert-level programming skills in languages commonly used in AI/ML, specifically Python.
Strong background in machine learning, particularly in natural language processing.
Experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing.
Excellent problem-solving skills and ability to tackle complex, novel challenges.
Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Proven track record of leading technical projects and mentoring junior engineers.
Nice to Haves:
Experience with reinforcement learning techniques applied to language models.
Familiarity with multi-modal AI systems (e.g., integrating text, image, and audio data).
Knowledge of AI ethics and experience implementing responsible AI practices.
Contributions to open-source NLP or information retrieval projects.
Experience with high-performance, low-latency systems.
Publications in peer-reviewed journals or conferences related to RAG, NLP, or information retrieval.
Experience with MLOps and CI/CD pipelines for AI systems.
Familiarity with knowledge graph technologies and their integration with RAG systems.
YOE Requirement:
12 yrs., B.S. or 10 yrs. w/ M.S., 4 yrs. of additional SWE experience may be substituted for a bachelor’s degree.
Clearance:
TS/SCI with polygraph
Clarity Innovations provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.
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Description:
We are seeking an experienced and innovative Senior RAG (Retrieval-Augmented Generation) Integration Software Engineer to lead our efforts in developing cutting-edge AI solutions. The ideal candidate will have a proven track record of designing, implementing, and optimizing RAG systems that seamlessly integrate information retrieval with advanced language generation models. This role requires a deep understanding of both traditional information retrieval techniques and state-of-the-art natural language processing. As a senior member of our team, you will be responsible for architecting robust RAG solutions, mentoring junior engineers, and driving technical decisions that shape the future of our AI-powered products. We are looking for a problem-solver who can adapt quickly to new challenges, communicate complex ideas effectively, and contribute to our culture of continuous learning and innovation.
Responsibilities:
Lead the design and implementation of scalable RAG systems that integrate seamlessly with our existing AI infrastructure.
Develop and optimize information retrieval algorithms to enhance the accuracy and relevance of generated content.
Implement and fine-tune large language models to work effectively within our RAG framework.
Create innovative solutions to combine retrieved information with generated text, ensuring coherent and contextually appropriate outputs.
Collaborate with cross-functional teams to integrate RAG capabilities into various products and services.
Mentor junior engineers and contribute to the technical growth of the team.
Stay abreast of the latest advancements in RAG, NLP, and related fields, and proactively incorporate new techniques into our systems.
Develop and maintain best practices for RAG system development, testing, and deployment.
Participate in code reviews, architectural discussions, and technical decision-making processes.
Interface with customers infrequently to gather product requirements and identify technical opportunities.
Skills Requirements:
Bachelor's degree in Computer Science, Artificial Intelligence, or a related field; advanced degree preferred.
12+ years of professional software engineering experience, with a strong focus on AI and NLP.
Extensive experience designing and implementing RAG systems or similar hybrid AI architectures.
Deep understanding of information retrieval techniques, including vector databases and embedding models.
Proficiency in working with and fine-tuning large language models.
Expert-level programming skills in languages commonly used in AI/ML, specifically Python.
Strong background in machine learning, particularly in natural language processing.
Experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing.
Excellent problem-solving skills and ability to tackle complex, novel challenges.
Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Proven track record of leading technical projects and mentoring junior engineers.
Nice to Haves:
Experience with reinforcement learning techniques applied to language models.
Familiarity with multi-modal AI systems (e.g., integrating text, image, and audio data).
Knowledge of AI ethics and experience implementing responsible AI practices.
Contributions to open-source NLP or information retrieval projects.
Experience with high-performance, low-latency systems.
Publications in peer-reviewed journals or conferences related to RAG, NLP, or information retrieval.
Experience with MLOps and CI/CD pipelines for AI systems.
Familiarity with knowledge graph technologies and their integration with RAG systems.
YOE Requirement:
12 yrs., B.S. or 10 yrs. w/ M.S., 4 yrs. of additional SWE experience may be substituted for a bachelor’s degree.
Clearance:
TS/SCI with polygraph
Clarity Innovations provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.
#J-18808-Ljbffr