Prompt Engineering Architect at Bright Vision Technologies

Fremont, California, United States -

Full Time

Start Date

Immediate

Expiry Date

29 Aug, 26

Salary

150000.0

Posted On

31 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Prompt Engineering, LLM Architecture, Agentic Workflows, Retrieval-Augmented Generation, Python, Vector Databases, Evaluation Frameworks, Responsible AI, Software Engineering, Prompt Design Patterns, Tool Use, Multi-step Reasoning, Chunking, Indexing, Reranking, Red-teaming

Industry

Information Technology & Services

Description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we’re looking for a skilled Prompt Engineering Architect to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Prompt Engineering Architect Location: 100% Remote (Continental United States) Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor) Salary: $100K - $150K Experience: 6+ years Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates. Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party) Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap Compensation: Competitive base salary commensurate with experience, plus benefits. Employment Terms & Visa Policy This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies. This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved. We do not engage in C2C, 1099, or third-party arrangements for this role. BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE. Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables. No new H1B sponsorship is available for this role. However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates. For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience. Job Summary We are looking for a Prompt Engineering Architect to define and lead the strategy, patterns, and tooling for designing prompts, agentic workflows, and LLM-based application architectures across the organization. The role combines deep practical mastery of modern LLMs with the discipline of building reusable design patterns, evaluation frameworks, and developer tooling that scale across many teams and use cases. The ideal candidate has shipped LLM-powered products in production, is fluent in prompt design patterns and agent architectures, and brings strong judgment about when and how to apply different LLM techniques responsibly. Key Responsibilities Define organization-wide standards, patterns, and reference architectures for LLM-based applications. Design prompt structures, instruction templates, and retrieval strategies for diverse production use cases. Architect agentic systems incorporating tool use, planning, memory, and multi-step reasoning. Lead the design of retrieval-augmented generation pipelines including chunking, indexing, and reranking strategies. Develop evaluation frameworks for prompt quality, agent reliability, and end-to-end task success. Build internal tooling and libraries that accelerate LLM application development across teams. Establish guardrails, safety filters, and policy enforcement patterns for LLM-powered products. Collaborate with model engineering teams on prompt-model co-design and fine-tuning opportunities. Conduct technical reviews of LLM application designs across multiple product teams. Mentor engineers and applied scientists on prompt engineering and LLM application architecture. Lead red-teaming exercises and continuously improve robustness against adversarial inputs. Track latency, cost, and quality trade-offs in LLM application design and recommend optimizations. Document patterns, anti-patterns, and lessons learned for broad internal reuse. Stay current with LLM capabilities, tooling, and research, and translate advances into practical guidance. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, or a related field. Six or more years of software engineering experience, with significant time on LLM-based applications. Demonstrated experience shipping LLM-powered products to production. Deep familiarity with modern LLM APIs and agent frameworks. Strong understanding of retrieval-augmented generation, embeddings, and vector databases. Experience designing evaluation pipelines for non-deterministic systems. Strong Python skills and comfort with modern application frameworks. Solid grasp of responsible AI principles, including safety and policy considerations. Excellent written and verbal communication skills. Track record of mentoring engineers and influencing technical direction. Preferred Qualifications Public writing, talks, or open-source contributions on LLM application development. Experience with multi-agent architectures and complex tool-use systems. Familiarity with fine-tuning workflows and when to choose them over prompting. Exposure to product domains such as customer support, coding assistants, or analytics agents. Experience integrating LLMs into enterprise software systems with strict compliance requirements. How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to hilda@bvteck.com Learn more about Bright Vision Technologies at www.bvteck.com. We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans. Position offered by “No Fee Agency.” Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Responsibilities

Define organization-wide standards and architectures for LLM-based applications and agentic systems. Lead the design of RAG pipelines, evaluation frameworks, and internal tooling to accelerate LLM development.