Vector Stores Engineer Jobs

1 job found

1d ago

Expert Consultant, Coro, AI Engineer

Bain & Co. Seattle, WA

Seattle, WA

1d ago

$129k - $172k/yr Full time Agentic Ai Ai Workflows Artificial Intelligence

Apply Now

Job Description

Location: Seattle, WA onsite; salary: USD 128,500 - 171,500 per year.

The AI Engineer role with Bain Coro focuses on building GenAI powered tools and agentic AI workflows for B2B Commercial Excellence, spanning from proof of concept to production deployments.

Responsibilities

Develop AI driven tools and products that deliver measurable business impact.
Architect GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern LLM stacks.
Deploy agentic workflows with clear value, including tool use, multi step execution, and human in the loop controls, prioritizing reliability and safety.
Design and implement advanced search, retrieval, and knowledge pipelines across diverse data stores (hybrid search, vector stores, graph databases / knowledge graphs, traditional platforms) covering indexing, metadata, relevance tuning, freshness, caching, access controls, and source attribution.
Build robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns.
Integrate solutions into enterprise environments and workflows via APIs, data systems, and collaboration tools while balancing quality, latency, cost, privacy, and adoption.
Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.
Develop and apply data science and machine learning capabilities to business problems.
Deliver end to end ML solutions: data preparation, feature engineering, model selection, training, validation, testing, and performance analysis.
Choose appropriate methods ranging from classical ML to deep learning, including sequence, text, and image models when relevant.
Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and documentation.
Demonstrate fluency with modern deep learning concepts such as transformer fundamentals and LLM pre training versus post training approaches including instruction tuning and preference optimization.
Engineer for production delivery: write clean, testable code and ship AI services through the full SDLC including build, test, deploy, monitor, and iterate.
Implement MLOps and GenAIOps practices: CI/CD, reproducibility, environment parity, model and prompt versioning, and readiness for operation.
Build evaluation and observability for GenAI and agentic systems: tracing, instrumentation, regression test suites, automated scoring, and iteration loops for prompts and policies.
Design for secure enterprise deployment: access controls, auditability, handling of sensitive and PII data, and guardrails for responsible AI.
Develop reusable components and accelerators (templates, evaluation harnesses, connectors, orchestration patterns) that scale across client contexts.
Engage in a client facing consulting environment: communicate clearly with technical and non technical stakeholders, lead sessions, present recommendations, and document technical details concisely.
Collaborate with Bain consultants to prioritize critical technical decisions that unlock business value.
Support proposal shaping and scoping: effort sizing, architecture options, risk assessment, and delivery roadmaps.

Requirements

3-5+ years of professional AI / ML engineering experience (or equivalent), with strong backend fundamentals.
Strong Python proficiency; experience building APIs / services (REST / gRPC) and integrating with enterprise systems.
Hands on experience building LLM powered applications with attention to latency, cost, reliability, and security.
Experience architecting advanced retrieval and search systems (hybrid retrieval, vector search, reranking) and working across data stores (vector, graph, relational, document, search).
Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) with modern frameworks (LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops, plus good judgment on when to apply agentic approaches.
Experience creating reusable skills, tools, and services (including MCP) for agent use, with schema validation (Pydantic) to enforce data contracts.
Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling.
Experience deploying and operating services on AWS, GCP, or Azure, including environment management, reliability, observability, and scaling.
Experience with Docker and Kubernetes and operating services in production environments.
Ability to implement security, privacy, and governance requirements for AI systems (authentication/authorization, access controls, PII handling, enterprise risk controls).
Experience training, validating, and testing ML models; solid understanding of overfitting, generalization, and evaluation methodologies.
Practical feature engineering and data preprocessing for real world datasets.
Familiarity with a broad set of ML algorithms (classical and deep learning) and ability to select methods that suit business and data constraints.
Familiarity with deep learning frameworks (PyTorch, TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
Proven ability to operate in ambiguity and complexity, manage priorities, and deliver outcomes independently or with a team.
Excellent interpersonal and communication skills; able to explain technical decisions to mixed audiences.
Strong stakeholder management; comfortable working directly with clients.
MBA or PhD in a technical field is preferred.
Background in consulting, professional services, or B2B analytics environments is preferred.
Experience collaborating with major AI ecosystem partners on real client deployments is preferred.

Technologies

Python
REST
gRPC
LangGraph
OpenAI Agents SDK
Pydantic AI
PyTorch
TensorFlow
Docker
Kubernetes
AWS
GCP
Azure
Vector stores
Graph databases
Knowledge graphs

Benefits

Health insurance (medical, dental, and vision) with Bain paying 100 percent of individual premiums
Generous paid time off including parental leave, sick leave, and holidays
Fully vested 401(k) company contribution
4.5 percent 401(k) company contribution with vesting after 3 years
Life and Long-Term Disability insurance
Annual fitness reimbursements
Annual discretionary performance bonus

View full job page →

Get Vector Stores Engineer Jobs alerts

New Vector Stores Engineer Jobs, daily.