Bridgewater, NJ

Engineer Jobs in Bridgewater, NJ

3 jobs found

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Today

Lead AI Engineer, Agentic AI Solutions

Bausch+Lomb Companies Inc. Bridgewater, NJ

Bridgewater, NJ

Today

$150k - $200k/yr Full time Marketing Agentic Ai Agentic Ai Security

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Job Description

Bridgewater, NJ hybrid role focused on delivering production-grade, agentic AI solutions that support commercial decision-making.

Responsibilities

Design, build, and operate production Applied agents across the commercial process: brand strategy, customer insights, personalized engagement, and closed-loop feedback, using foundational agents rather than rebuilding.
Build performance investigation agents that autonomously decompose brand performance shifts across geography, channel, payer, and Eye Care Professional (ECP) segment; return sourced, reproducible narratives for brand and insights teams.
Build pre-call, post-call, and next-best-action / next-best-engagement agents that assemble ECP briefs from Glimpse (Next Best Action) platform and/or CRM; attach explainable reasoning to recommendations and write structured data back to CRM.
Build measurement and feedback agents to support A/B and multivariate test design, readout, and write-back into the planning loop.
Ground agents in the enterprise semantic layer and commercial knowledge graph so metric definitions, joins, grain, and row- and role-level access are resolved prior to query generation.
Implement determinism and reproducibility controls, including validate-then-lock specification patterns, ensuring repeated runs produce the same results for auditable decisions.
Integrate agents with enterprise systems including Glimpse (NBA platform) / Veeva or Salesforce, Adobe, and internal commercial platforms using Model Context Protocol (MCP), agent-to-agent (A2A) patterns, tool discovery, scoped authentication, and structured outputs.
Create and maintain agent evaluation harnesses: golden datasets, calibrated LLM-as-judge scoring, and regression testing; track agent KPIs for task completion, grounding, reproducibility, human-override rate, latency, and cost per task.
Operate with bounded autonomy: agents prepare, propose, investigate, summarize, and route while humans in the loop approve claims, privacy-sensitive actions, and validated-record changes.
Own production operations including observability and tracing, Evals, token and cost controls (loop caps, model routing and fallback, latency budgets), versioning, rollback, on-call response, and postmortems.
Partner with Medical, Legal, Regulatory, Privacy, Compliance, and IT to incorporate Responsible AI standards during design.
Collaborate with brand teams, field operations, market access, and commercial analytics to translate business asks into agent specifications tied to a defined decision; decline use cases where an agent is the wrong tool.
Participate in Agile AI Operations: backlog management, sprint planning, cross-functional collaboration, and continuous improvement.
Contribute reusable patterns, components, and documentation to a shared agent pattern library; mentor engineers and analysts adopting them.

Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field.
5+ years of experience building and deploying production software, AI, or ML solutions, including LLM-powered applications.
Strong Python development and software engineering best practices: testing, CI/CD, APIs, code reviews, and containerization.
Hands-on experience with AI agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or similar.
Experience with tool calling, structured outputs, function schemas, and enterprise system integrations.
Experience designing and implementing RAG solutions, vector databases, embeddings, and retrieval systems.
Strong SQL and data modeling skills, including defining and validating business metrics.
Experience developing frameworks and metrics to evaluate AI/LLM performance.
Experience with cloud and MLOps platforms such as AWS, Azure, Databricks, Snowflake, and orchestration tools.
Experience operating in regulated environments with governance, compliance, and auditability focus.
Proven ability to collaborate effectively across technical and business functions.
Experience working in Agile environments using Scrum, SAFe, or similar methodologies.
Strong communication and presentation skills for non-technical audiences.

Preferred

Experience with pharmaceutical, medical device, or consumer health commercial data, including prescription, claims, payer, CRM, and sales data.
Familiarity with eye care industry dynamics (ophthalmology, optometry, and ECP channels).
Experience with Veeva and/or Salesforce integrations.
Experience with knowledge graphs, semantic modeling, and semantic layer tools.
Familiarity with healthcare compliance requirements including HIPAA, GDPR, FDA promotional regulations, and MLR/PRC review processes.
Experience with LLM observability, monitoring, and AI cost management.
Experience in regulated industries with strong governance, auditability, and compliance requirements.

Technology

Python
Azure / AWS, Databricks, Snowflake
LLMs, Agentic AI
RAG, vector databases, embeddings, retrieval systems
Salesforce, Veeva, CRM, Adobe, Glimpse
LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex
Model Context Protocol (MCP), model routing, A2A patterns, tool discovery, structured outputs, function schemas
Knowledge graphs, semantic layer
SQL, CI/CD, A/B testing, multivariate testing
Evals, containerization, MLOps
Scrum, SAFe

Benefits

Medical, dental, vision insurance
Disability and life insurance
401(k) plan and company match
Tuition reimbursement program (select degrees)
Company holidays
Well-being benefits
Sick time
Floating holidays
Paid vacation
U.S. based employees may be eligible for short-term and/or long-term incentives

Location and Work Model

Bridgewater, NJ (hybrid)
Eligible for hybrid schedule allowing up to 2 days/week telecommuting and 3 days/week in the Bridgewater, NJ corporate office

Compensation

USD 150,000 - 200,000 per year (starting pay range)
Actual base salary may vary based on factors; estimated range reflects anticipated range for the position

Authorization to Work

Applicants must be authorized to work for any employer in the U.S.
Company is unable to sponsor or take over sponsorship of an employment Visa at this time

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Today

Lead AI Engineer, Knowledge & Semantic Systems

Bausch + Lomb Bridgewater, NJ

Bridgewater, NJ

Today

$150k - $200k/yr Full time Artificial Intelligence Data Architecture Data Engineer

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Job Description

The Lead AI Engineer, Knowledge & Semantic Systems is an individual contributor role focused on designing governed foundational data, knowledge, and retrieval systems that support enterprise AI solutions. This position emphasizes semantic modeling, knowledge graph development, metadata frameworks, and retrieval capabilities for accurate, scalable, and compliant AI-driven insights.

Location and Work Schedule

Location: Bridgewater, NJ (onsite)
Hybrid eligibility: Up to 2 days/week telecommuting from home and 3 days/week in the Bridgewater, NJ corporate office

Compensation

Salary: USD 150,000 - 200,000 per yearly

Role Summary

This role builds and maintains governed semantic and retrieval systems that enable agents and BI to use consistent, certified definitions. Responsibilities include establishing canonical metric definitions, extending a commercial ontology and knowledge graph, enforcing semantic constraints, and operating an end-to-end retrieval stack. The position also partners closely with Applied AI Agents engineers to drive measurable improvements in agent answer accuracy and delivery velocity.

Responsibilities

Design, build, and maintain a governed semantic layer for commercial metrics, including canonical metric definitions, dimensions, hierarchies, joins, grain, and row- and role-level access policy so agents and BI consume certified definitions.
Codify commercial metric definitions such as TRx, NRx, NBRx, NC TRx, market share and market basket, decile and segment assignment, and projected versus captured volume, including source system, calculation approach, refresh cadence, and known limitations.
Arbitrate conflicting metric definitions across brand, field, market access, and finance.
Implement constraints that prevent semantically misleading queries, such as blending projected and actual volumes, mixing incompatible grains, or computing share across non-comparable sources.
Design and extend the commercial ontology and knowledge graph, covering ECP, account, affiliation and parent-child hierarchy, payer and plan, formulary status, product, territory and alignment, content asset, and engagement.
Apply entity resolution across sources used by agents, reconciling prescriber and account identity across prescription, claims, specialty pharmacy, and CRM feeds while maintaining group practice and affiliation structures.
Maintain taxonomies, controlled vocabularies, and synonym and alias mappings to ensure varied business phrasing resolves consistently to governed concepts.
Encode temporal validity for territory realignments, formulary changes, affiliation changes, and segment refreshes to support historically correct answers.
Own the retrieval stack end to end, including chunking strategy, embedding model selection and evaluation, and index configuration and tuning.
Treat retrieval quality as a measured discipline by building labeled query sets and tracking recall and precision at k, groundedness, and citation accuracy, supported by regression testing.
Manage reindexing, embedding drift, model migration, and vector infrastructure cost and performance at production scale.
Expose semantic and retrieval capabilities to agents through well-specified interfaces, including Model Context Protocol (MCP) servers and resources, tool contracts, and structured schemas with disambiguation hints, synonym maps, and worked examples.
Partner with Applied AI Agents engineers as the primary upstream dependency, working on a shared sprint cadence and contributing to agent answer accuracy and delivery velocity.
Diagnose grounding failures by determining whether issues originate from definition, entity resolution, retrieval, or model reasoning, and remediate within the layer.
Operate a federated contribution model by reviewing proposed metrics, entities, and relationships and curating the canonical model to extend without fragmentation.
Partner with Data Engineering, IT, Privacy, and Compliance to enforce access policy, PDRP and HIPAA minimum-necessary handling, and audit trails at the definition and retrieval layer.
Document and socialize the model and run enablement so analysts and engineers adopt governed definitions instead of rebuilding them locally.

Requirements

Bachelor's or Master's degree in Computer Science, Data Engineering, Information Science, Machine Learning, or a related field
5+ years of experience in data engineering, analytics, semantic modeling, or knowledge engineering
Expertise in SQL, dimensional data modeling, and business metric governance
Hands-on experience with semantic layer tools (e.g., dbt Semantic Layer, MetricFlow, Cube, LookML, AtScale)
Experience designing and managing knowledge graphs, ontologies, and graph databases (e.g., Neo4j)
Experience with entity resolution, identity management, and master data concepts
Experience with vector databases, retrieval systems, and search optimization
Understanding of LLM-enabled solutions, including RAG, tool calling, structured outputs, and MCP
Strong Python development skills and software engineering best practices (CI/CD, testing, version control, containerization)
Experience with cloud data platforms and tools such as Snowflake, Databricks, AWS/Azure, dbt, Airflow, or Dagster
Knowledge of data governance, security, lineage, and compliance requirements
Proven ability to collaborate effectively across business and technical teams
Experience working in Agile environments using Scrum, SAFe, or similar methodologies
Excellent communication and documentation skills, including the ability to align stakeholders on data definitions and standards

Technologies

Python, SQL
Azure, AWS, Databricks, Snowflake
Knowledge Graphs, Semantic Modeling
Vector Databases, Retrieval Systems
dbt Semantic Layer, MetricFlow, Cube, LookML, AtScale
Neo4j
LLM-enabled solutions, RAG, tool calling, structured outputs, MCP
CI/CD, testing, version control, containerization
dbt, Airflow, Dagster
Scrum, SAFe, PDRP, HIPAA

Benefits

Medical, dental, vision insurance
Disability and life insurance
401(k) plan and company match
Tuition reimbursement program (select degrees)
Company holidays
Well-being benefits
Sick time
Floating holidays
Paid vacation
Short-term and/or long-term incentives

Preferred

Experience with pharmaceutical commercial data, including prescription, claims, payer, specialty pharmacy, hub, and CRM data
Familiarity with eye care industry dynamics, including ophthalmology, optometry, and Eye Care Professional (ECP) networks
Experience with customer master data management (MDM) and HCP/HCO data in life sciences
Experience with graph databases (e.g., Neo4j) and vector database technologies
Familiarity with content metadata, classification, and approval workflows
Experience with data governance, cataloging, lineage, and data observability tools
Knowledge of healthcare compliance requirements, including HIPAA and FDA promotional regulations
Experience working in regulated industries with strong audit and compliance standards

Additional Information

Applicants must be authorized to work for any employer in the U.S. The company is unable to sponsor or take over sponsorship of an employment Visa at this time.

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3mo ago

Analytics Engineer - AI Trainer

DataAnnotation Bridgewater, NJ 🇺🇸 Remote

Bridgewater, NJ

3mo ago Closed

$50 - $100/hr Contract Ai Ml Ai Training Analyst

This position is no longer accepting applications (closed Aug 16, 2026).

Job Description

DataAnnotation seeks an Analytics Engineer - AI Trainer in Bridgewater, NJ, offering remote work options for a contract role with flexible scheduling.

Responsibilities

Assess AI produced quantitative work including statistics, predictive modeling, scientific reasoning, and data driven insights for accuracy and real world validity.
Create and solve quantitative tasks used to train and benchmark AI systems, covering forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and well documented analytical code.
Deliver actionable feedback that shapes the next generation of AI models focused on quantitative reasoning.

Requirements

Minimum of 3 years in a hands on quantitative role or research environment (data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields).
Some coding experience with the ability to write and review analytical code end to end.
Practical experience with statistical methods, predictive modeling, and experiment design (A/B testing, hypothesis testing, regression, classification, time series forecasting).
Fluency in English with strong writing skills.
Bachelor's degree in a quantitative field preferred (Statistics, Computer Science, Mathematics, Engineering or similar); advanced degree (Master's or PhD) is a plus.
Relevant credentials are a plus (for example Kaggle competition ranking, AWS or GCP ML certifications, or equivalent demonstrated expertise).

Technologies

AWS
GCP
Kaggle

Compensation

Hourly rate: USD 50 - 100 per hour.

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose projects and hours on your own terms from your home computer.
Competitive pay with potential bonus rates on select projects.
Impact: contribute to AI systems designed to reason about data and analytics.

Note

Payment is processed via PayPal. We will never ask for money from you.
Geographic eligibility: open to candidates in the US, Canada, UK, Ireland, Australia, and New Zealand.

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Engineer Jobs in Bridgewater, NJ

Lead AI Engineer, Agentic AI Solutions

Lead AI Engineer, Knowledge & Semantic Systems

Analytics Engineer - AI Trainer

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