Senior Agentic AI Engineer

Posted 2 Hours Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
Hybrid
Senior level
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
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The Role
Lead design and delivery of retrieval-augmented generation and agentic AI solutions: translate stakeholder needs into data science and retrieval problem statements, build ML and retrieval models, design RAG patterns, ensure secure enterprise data access and governance, evaluate retrieval and grounding quality, and integrate retrieval systems with orchestration and platform components.
Summary Generated by Built In
Job Description
At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
Overview
As a leading global aerospace company, Boeing develops, manufactures and services commercial airplanes, defense products and space systems for customers in more than 150 countries. As a top U.S. exporter, the company leverages the talents of a global supplier base to advance economic opportunity, sustainability and community impact. Boeing's team is committed to innovating for the future, leading with sustainability, and cultivating a culture based on the company's core values of safety, quality and integrity.
Technology for today and tomorrow
The Boeing India Engineering & Technology Center (BIETC) is a 5500+ engineering workforce that contributes to global aerospace growth. Our engineers deliver cutting-edge R&D, innovation, and high-quality engineering work in global markets, and leverage new-age technologies such as AI/ML, IIoT, Cloud, Model-Based Engineering, and Additive Manufacturing, shaping the future of aerospace.
People-driven culture
At Boeing, we believe creativity and innovation thrives when every employee is trusted, empowered, and has the flexibility to choose, grow, learn, and explore. We offer variable arrangements depending upon business and customer needs, and professional pursuits that offer greater flexibility in the way our people work. We also believe that collaboration, frequent team engagements, and face-to-face meetings bring together different perspectives and thoughts - enabling every voice to be heard and every perspective to be respected. No matter where or how our teammates work, we are committed to positively shaping people's careers and being thoughtful about employee wellbeing.
With us, you can create and contribute to what matters most in your career, community, country, and world. Join us in powering the progress of global aerospace.
The Agentic AI Strike Team within Boeing's Enterprise AI & Data organization are seeking a motivated Senior Agentic AI Engineer to join our team at Boeing. This role follows the traditional data scientist skillset but emphasizes experience and capabilities for retrieval-augmented generation (RAG) and agentic AI workflows. You will work with business stakeholders across Boeing to decompose complex problems, develop high-quality data-driven models and retrieval strategies, and deploy solutions that enable AI agents to securely and effectively use enterprise data in decision-making and workflows.
This role will be based out of Bangalore, India.
Position Responsibilities:
  • Collaborate with business stakeholders to understand project requirements and objectives and to translate vague business needs into clear data science and retrieval problem statements.
  • Decompose complex problems into manageable tasks and develop end-to-end data-driven solutions architect that include modeling, retrieval, and integration into workflows, leading the way from capabilities to solutioning
  • Should demonstrate strong communication and business development skills, lead Business transformation strategies, workshops with business stakeholders in defining strategic needs, develop AI/Agentic AI roadmap to deliver on key business KPIs
  • Determine and develop the most appropriate machine learning and retrieval models (classification, regression, unsupervised methods, and retrieval pipelines) to resolve business problems
  • Design and optimize retrieval-augmented generation (RAG) patterns that support agent workflows and decision-making.
  • Define retrieval strategies for enterprise content sources, structured data, unstructured documents, and operational systems.
  • Partner with platform engineers and data owners to enable secure access to approved knowledge sources.
  • Develop methods for context selection, ranking, filtering, summarization, and grounding to improve response quality.
  • Evaluate retrieval performance, relevance, latency, and answer fidelity across use cases.
  • Create testing and benchmarking approaches for retrieval quality and downstream agent outcomes.
  • Help define guardrails for data access, permissions, privacy, and information sensitivity.
  • Work with governance and security stakeholders to ensure enterprise data is used in a compliant and auditable way.
  • Contribute to reusable patterns, standards, and documentation for RAG-enabled agent capabilities.
  • Support integration of retrieval systems with orchestration frameworks, APIs, and AI platform components.

Employer will not sponsor applicants for employment visa status.
Basic Qualifications (Required Skills/Experience):
  • Demonstrated experience working with stakeholders to create data science problem statements from vague business requirements.
  • Strong understanding and hands-on experience with natural language processing (NLP) techniques (tokenization, embedding generation, summarization, named entity extraction, etc.).
  • Familiarity with large language models and their applications in retrieval-augmented generation and agent workflows.
  • Practical experience developing machine learning regression and multi-class classification models, especially under imbalanced data conditions.
  • Demonstrated experience with RAG architectures and retrieval systems in production or enterprise environments.
  • Strong understanding of how LLMs use retrieved context within agent workflows.
  • Familiarity with retrieval concepts such as chunking, embeddings, vector search, metadata filtering, hybrid retrieval, reranking, and query rewriting.
  • Ability to evaluate retrieval quality and answer grounding for accuracy and relevance.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills.
  • Ability to work effectively across development, data, product, and governance teams.
  • Experience with data access controls, privacy, and security considerations.
  • Proficiency working with configuration and data formats such as Python, JSON, and YAML.

Preferred Qualifications (Desired Skills/Experience):
  • Experience enabling agentic RAG or retrieval-driven workflow automation.
  • Familiarity with enterprise search platforms, vector databases (e.g., Pinecone, Milvus, Weaviate), and knowledge retrieval pipelines.
  • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar tools.
  • Knowledge of hybrid retrieval methods combining keyword and semantic search.
  • Experience with observability, tracing, and evaluation for retrieval and generation pipelines.
  • Familiarity with retrieval benchmarking, relevance scoring, and human evaluation workflows.
  • Experience with document parsing, knowledge ingestion, and content normalization.
  • Understanding of prompt design patterns that improve grounding and citation quality.
  • Experience with security, compliance, and data governance controls in enterprise AI systems.
  • Experience working in regulated or large-scale enterprise environments.

Typical Education & Experience:
  • Typically, 12-16 years' related work experience or relevant military experience. Advanced degree (e.g. Bachelor, Master, etc.) preferred but not required.

Relocation:
This position does offer relocation within INDIA.
Applications for this position will be accepted until Jul. 12, 2026
Export Control Requirements:
This is not an Export Control position.
Relocation
This position offers relocation based on candidate eligibility.
Visa Sponsorship
Employer will not sponsor applicants for employment visa status.
Shift
Not a Shift Worker (India)
Equal Opportunity Employer:
We are an equal opportunity employer. We do not accept unlawful discrimination in our recruitment or employment practices on any grounds including but not limited to; race, color, ethnicity, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military and veteran status, or other characteristics covered by applicable law.
We have teams in more than 65 countries, and each person plays a role in helping us become one of the world's most innovative, diverse and inclusive companies. We are proud members of the Valuable 500 and welcome applications from candidates with disabilities. Applicants are encouraged to share with our recruitment team any accommodations required during the recruitment process. Accommodations may include but are not limited to: conducting interviews in accessible locations that accommodate mobility needs, encouraging candidates to bring and use any existing assistive technology such as screen readers and offering flexible interview formats such as virtual or phone interviews.
#BI-Hybrid

Skills Required

  • Demonstrated experience converting vague business requirements into data science problem statements
  • Hands-on experience with NLP techniques (tokenization, embedding generation, summarization, NER)
  • Familiarity with large language models and their use in RAG and agent workflows
  • Practical experience developing machine learning regression and multi-class classification models, including imbalanced data handling
  • Demonstrated experience with RAG architectures and retrieval systems in production or enterprise environments
  • Understanding of how LLMs use retrieved context within agent workflows
  • Familiarity with retrieval concepts: chunking, embeddings, vector search, metadata filtering, hybrid retrieval, reranking, query rewriting
  • Ability to evaluate retrieval quality and answer grounding for accuracy and relevance
  • Strong analytical and problem-solving skills
  • Excellent written and verbal communication skills
  • Ability to work effectively across development, data, product, and governance teams
  • Experience with data access controls, privacy, and security considerations
  • Proficiency with configuration and data formats such as Python, JSON, and YAML
  • Typically 12-16 years related work experience or relevant military experience (advanced degree preferred but not required)
  • Experience enabling agentic RAG or retrieval-driven workflow automation
  • Familiarity with enterprise search platforms and vector DBs (e.g., Pinecone, Milvus, Weaviate)
  • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel
  • Knowledge of hybrid retrieval methods combining keyword and semantic search
  • Experience with observability, tracing, and evaluation for retrieval and generation pipelines
  • Familiarity with retrieval benchmarking, relevance scoring, and human evaluation workflows
  • Experience with document parsing, knowledge ingestion, and content normalization
  • Understanding of prompt design patterns that improve grounding and citation quality
  • Experience with security, compliance, and data governance controls in enterprise AI systems
  • Experience working in regulated or large-scale enterprise environments

What the Team is Saying

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Boeing Compensation & Benefits Highlights

  • Retirement Support For most U.S. nonunion roles, the company matches 401(k) contributions with immediate vesting, and a student‑loan feature counts eligible payments toward earning the company match. Some union agreements also include robust retirement terms, combining a match up to a set percentage with an additional company contribution.
  • Parental & Family Support Paid parental leave is provided at full pay for birth, adoption, surrogacy, or foster placement, alongside adoption and surrogacy assistance. Family resources such as specialized health programs and backup child and elder care are available.
  • Healthcare Strength Coverage spans medical, dental, and vision plus mental‑health and specialty clinical programs (e.g., cancer support and centers of excellence), with many benefits beginning soon after hire. Virtual care, coaching, and access to licensed therapists are included.

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The Company
HQ: Arlington, VA
170,000 Employees
Year Founded: 1916

What We Do

A leading global aerospace company and top U.S. exporter, Boeing develops, manufactures and services commercial airplanes, defense products and space systems for customers in more than 150 countries. Our U.S. and global workforce and supplier base drive innovation, economic opportunity, sustainability and community impact. Boeing is committed to fostering a culture based on our core values of safety, quality and integrity.

Why Work With Us

Aerospace protects and connects people, enables economic growth and trade, provides humanitarian relief and allows for human exploration of space. Boeing collaborates globally to support responsible growth for our industry, and we invest in innovation that improves the efficiency and sustainability of air travel and our operations.

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