senior data engineer

Blue Orange Digital

<div><h3 class="jobSectionHeader"><b>Company overview:</b></h3><p>
Blue Orange Digital is a boutique data &amp; AI consultancy that delivers enterprise-grade results. We design and build modern data platforms, analytics, and ML/AI Agent solutions for mid‑market and enterprise clients across Private Equity, Financial Services, Healthcare, and Retail.</p><p>
Our teams work with technologies like Databricks, Snowflake, dbt, and the broader Microsoft ecosystem to turn messy, real-world data into trustworthy, actionable insight.</p><p>
We&rsquo;re a builder‑led, client‑first culture that prizes ownership, clear communication, and shipping high‑impact work.</p><p><b>
Note</b>: Please submit your resume in English, as all application materials must be in English for review and consideration.</p><h3 class="jobSectionHeader"><b>
Position overview:</b></h3><p>
The ideal candidate is a US-based Senior Data Engineer who can step into an established enterprise data warehouse environment as a hands-on contributor and a peer-level thought partner to the client's data leadership. This role requires someone who can hit the ground running on a complex Oracle and Oracle Cloud Infrastructure (OCI) stack, plus AWS, bring opinionated patterns and alternatives to the table, and operate independently without day-to-day direction.</p><p>
The successful candidate will balance maintaining a stable, well-established production environment with helping shape the next generation of the platform, including the team's adoption of Apache Iceberg, lakehouse patterns, and cloud-native ETL.</p><p><b>
Note</b>: This is a contractor role with potential expansion to full‑time employment, depending on performance and business needs.</p><h3 class="jobSectionHeader"><b>
Responsibilities:</b></h3><ul><li><p>
Build and maintain data flow and transformation patterns across an enterprise Oracle data warehouse environment.</p></li><li><p>
Partner with the client database and platform teams to manage external tables, flat files, and high-volume batch ingestion.</p></li><li><p>
Identify and implement performance optimizations at the storage, query, and orchestration layers, including across a long-standing production warehouse with accumulated business logic.</p></li><li><p>
Maintain and extend cloud-to-Oracle integration patterns, the data catalog layer, and shell-script-based orchestration jobs.</p></li><li><p>
Operate and evolve the existing ETL stack while contributing to the evaluation and adoption of Oracle-native data transform tools.</p></li><li><p>
Contribute hands-on to the buildout of a hybrid lakehouse using Apache Iceberg, OCI Object Storage, Parquet, and external table patterns.</p></li><li><p>
Prepare for an upcoming shift in source ingestion toward cloud object storage and a data lake delivery pattern.</p></li><li><p>
Perform light Linux server administration and performance tuning on existing ETL infrastructure.</p></li><li><p>
Act as a collaborative thought partner with senior client stakeholders, proposing alternatives and surfacing patterns rather than waiting for prescriptive direction.</p></li><li><p>
Support potential future workstreams including master data management and golden record initiatives once data foundations are matured.</p></li></ul><h3 class="jobSectionHeader"><b>
Requirements:</b></h3><ul><li><p>
5+ years of hands-on data engineering experience in Oracle-centric enterprise data warehouse environments.</p></li><li><p>
Current, hands-on experience with Oracle Cloud Infrastructure (OCI), specifically OCI Object Storage, OCI Data Transforms, Oracle Data Catalog, and OCI ETL patterns. Candidates needing ramp-up on OCI fundamentals will not be considered.</p></li><li><p>
Strong Oracle expertise, including advanced SQL, complex joins, performance tuning, and the ability to navigate a mature data warehouse with significant legacy business logic.</p></li><li><p>
Dimensional modeling proficiency, including star schemas, facts and dimensions, and slowly changing dimensions.</p></li><li><p>
Working knowledge of lakehouse concepts, including the role of object storage in a hybrid data warehouse and lakehouse architecture.</p></li><li><p>
Solid core ETL and ELT skills, including orchestration, error handling, dependency management, and high-volume batch ingestion.</p></li><li><p>
Working knowledge of Linux, including shell scripting, SSH-based administration, and basic server maintenance.</p></li><li><p>
Working knowledge of Java sufficient to read, debug, and lightly modify Java-based ETL components.</p></li><li><p>
Excellent written and verbal communication. Able to operate as a peer-level collaborator with senior client subject matter experts.</p></li><li><p>
US-based with Eastern Time business-hours overlap.</p></li></ul><h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul><li><p>
Hands-on Apache Iceberg experience, including table format, metadata layer, and migration patterns.</p></li><li><p>
Production Pentaho experience.</p></li><li><p>
Experience with AWS S3 to Oracle ingestion patterns and cloud-to-warehouse data lake integration.</p></li><li><p>
Exposure to high-volume transactional reporting domains.</p></li><li><p>
Master Data Management or golden record program experience.</p></li><li><p>
Background in data warehouse modernization or lakehouse migration projects.</p></li></ul><p><b>
Compensation</b>: $126,000 &ndash; $147,000 USD/year (or $10,500 &ndash; $12,250 USD/month)</p><p>
Background checks may be required for certain positions/projects.</p><p>
Blue Orange Digital is an equal-opportunity employer.</p></div>

Senior Data Engineer

Tavily

<div><div><p><b>About Tavily</b><br>
<br>
We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent - but also informed.</p>
<p>
We work with some of the most innovative teams in AI - from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world.</p>
<p><b>
Role:</b></p>
</div>
<p>We are looking for a Senior Business Systems Engineer to own our GTM Operations systems and strategy. You will have an integral role in architecting the engine that powers Tavily's growth. You will be our first hire to this team, building a seamless, scalable GTM stack and ensuring our data architecture supports world-class execution across Sales, Marketing, and Finance.</p>
<ul>
<li>Own the end-to-end technical architecture of the GTM tech stack, ensuring seamless data flow across the entire customer lifecycle&mdash;from initial marketing lead to sales conversion and customer success renewal. We will be implementing a fresh SFDC instance which you will help create from the ground up.</li>
</ul><ul><li>Serve as the primary technical liaison for Sales, Finance, and Marketing leadership, translating complex departmental requirements into a multi-quarter technical roadmap for the Force.com platform and integrated ecosystem.</li>
</ul><ul><li>Establish and enforce rigorous engineering standards, including automated testing and security protocols to ensure the reliability and integrity of internal GTM applications.</li>
</ul>
<p><b>What We're Looking For (Must Have):</b></p>
<ul>
<li>6+ years of Force.com development experience with a deep understanding of Apex, LWC, and platform limits.</li>
</ul><ul><li>Proven track record of designing complex enterprise integrations and managing high-volume data pipelines.</li>
</ul><ul><li>BS/MS in Computer Science, Computer Engineering, or a related technical field.</li>
</ul><ul><li>Ability to navigate complex relational databases and leverage data for strategic decision-making.</li>
</ul><ul><li>Experience with Agile methodologies and managing a prioritized backlog in Jira or similar tools.</li>
</ul>
<p><b>Nice to have:</b></p>
<ul>
<li>Salesforce Certified Application or System Architect.</li>
</ul><ul><li>Deep experience with CPQ and Billing, Stripe, or Netsuite integrations.</li>
</ul><ul><li>Advanced expertise in Integration Platforms like Workato, Zapier or Mulesoft.</li></ul></div>

Senior Business Systems Engineer (Agentic Search)

Fusemachines

<div>
 <strong>
  About Fusemachines
  <br/>
  <br/>
 </strong>
 Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 <br/>
 <br/>
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 <br/>
 <br/>
 <strong>
  Type: Full-time, Remote
  <br/>
  <br/>
 </strong>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We&rsquo;re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You&rsquo;ll work across the ML lifecycle&mdash;from problem framing and data exploration to model development, evaluation, deployment, and monitoring&mdash;often in partnership with client stakeholders and internal delivery teams.
 <br/>
 <br/>
 You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Problem Framing &amp; Stakeholder Partnership
  </li>
  <ul>
   <li>
    Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)
   </li>
   <li>
    Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)
   </li>
  </ul>
  <li>
   Data Analysis &amp; Feature Engineering
  </li>
  <ul>
   <li>
    Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses
   </li>
   <li>
    Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices
   </li>
   <li>
    Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions
   </li>
  </ul>
  <li>
   Model Development (Core ML)
  </li>
  <ul>
   <li>
    Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)
   </li>
   <li>
    Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation
   </li>
   <li>
    Build time series models (statistical and ML/DL approaches) and validate with proper backtesting
   </li>
   <li>
    Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness
   </li>
   <li>
    Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making
   </li>
  </ul>
  <li>
   Deep Learning
  </li>
  <ul>
   <li>
    Build and train deep learning models using PyTorch or TensorFlow/Keras
   </li>
   <li>
    Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)
   </li>
  </ul>
  <li>
   Evaluation, Explainability, and Iteration
  </li>
  <ul>
   <li>
    Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports
   </li>
   <li>
    Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence
   </li>
  </ul>
  <li>
   Productionization &amp; MLOps (Project-Dependent)
  </li>
  <ul>
   <li>
    Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration
   </li>
   <li>
    Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans
   </li>
  </ul>
  <li>
   Documentation &amp; Communication
  </li>
  <ul>
   <li>
    Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders
   </li>
   <li>
    Create documentation and lightweight demos that make results actionable
    <br/>
   </li>
  </ul>
 </ul>
 Success in This Role Looks Like
 <br/>
 <br/>
 <ul>
  <li>
   You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)
  </li>
  <li>
   Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring
  </li>
  <li>
   Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)
  </li>
  <li>
   Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)
  </li>
  <li>
   Strong SQL skills (joins, window functions, aggregation, performance awareness)
  </li>
  <li>
   Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset
  </li>
  <li>
   Hands-on experience across multiple model types, including:
  </li>
  <ul>
   <li>
    Classification &amp; regression
   </li>
   <li>
    Time series forecasting
   </li>
   <li>
    Clustering/segmentation
   </li>
  </ul>
  <li>
   Experience with deep learning in PyTorch or TensorFlow/Keras
  </li>
  <li>
   Strong problem-solving skills: ability to work with ambiguous goals and messy data
  </li>
  <li>
   Clear communication skills and ability to translate analysis into decisions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)
  </li>
  <li>
   Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)
  </li>
  <li>
   Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)
  </li>
  <li>
   Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)
  </li>
  <li>
   Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)
  </li>
  <li>
   Consulting or client-facing delivery experience
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Certifications (Strong Plus)
  <br/>
  <br/>
 </strong>
 Candidates with at least one relevant certification are especially encouraged to apply:
 <br/>
 <br/>
 <ul>
  <li>
   Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks)
  </li>
  <li>
   Databricks certifications (Data Scientist, Data Engineer, or related)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)
  </li>
  <li>
   Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products
  </li>
  <li>
   Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  <em>
   Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
   <br/>
   <br/>
  </em>
 </em>
 Important: Immigration Sponsorship Policy
 <br/>
 <br/>
 Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including:
 <br/>
 <br/>
 <ul>
  <li>
   Direct Company Sponsorship: Such as H-1B, J-1, or TN visas
  </li>
  <li>
   Employer of Record: Listing Fusemachines as the immigration employer on any government documentation
  </li>
  <li>
   Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT)
   <br/>
   <br/>
  </li>
 </ul>
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</div>


Machine Learning Engineer / Data Scientist

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<div><div><div>The Chief Data and Analytics Office (CDAO) is responsible for building enterprise-scale, cutting-edge platforms for AI/ML and data operations that are used firmwide across JPMorganChase.</div></div><div><div>
</div></div><div><div>As an AI Product Manager (Senior Associate) within our governance organization, you will understand, formulate and execute well-designed, user-friendly product features that encompass AI &amp; data governance frameworks, policies, and procedures. Your role is crucial in ensuring the ethical and compliant application of AI and data technologies across the entire firm. You will be instrumental in integrating AI/ML &amp; Data Management technology into the company's structure, adhering to sustainable best practices in compliance with JPMC technology, operational risk, and relevant regulations. Collaborating with cross-functional teams such as Firmwide CDO, data scientists, engineers, design, legal, compliance, strategy and business units, you will work on AI &amp; data governance initiatives and ensure they align with regulatory requirements and industry best practices.</div></div><div><div>
</div></div><div><div><b>Job Responsibilities</b></div></div><div><ul><li><div>
Design and implement product features that apply evolving AI &amp; data governance frameworks, policies, and procedures to ensure the ethical and responsible use of AI technologies across the organization, ensuring compliance with regulations, standards, guidelines, and emerging regulations.</div></li></ul></div><div><ul><li><div>
Leverage AI-assisted rapid prototyping techniques to validate product requirements, accelerating stakeholder alignment and product discovery.</div></li></ul></div><div><ul><li><div>
Support the product roadmap and backlog; author PRDs and acceptance criteria; define and track KPIs/OKRs to measure adoption, control coverage, lifecycle compliance and streamlined governance.</div></li></ul></div><div><ul><li><div>
Translate AI and data risk into produce requirements and control points embedded into the development lifecycle including model onboarding, model lineage and modification tracking, and agentic systems, data and model risk governance.</div></li></ul></div><div><ul><li><div>
Collaborate with cross-functional stakeholders such as Firmwide CDO, data scientists, engineers, legal, compliance, design and business units to integrate AI &amp; Data governance practices into the AI/ML &amp; data development lifecycle
</div></li></ul></div><div><ul><li><div>Establish monitoring and reporting mechanisms to track compliance with AI &amp; data governance policies and identify areas for improvement.
</div></li></ul></div><div><ul><li><div>Present product updates, risk management and governance findings, and recommendations to senior leaders and stakeholders, ensuring transparency and accountability.</div></li></ul></div><div><div>
</div></div><div><div><b>Required qualifications, capabilities and skills</b></div></div><div><ul><li><div>
3+ years of experience in product management, technology governance, risk management, or compliance within regulated industries such as financial services, with a focus on Artificial Intelligence</div></li></ul></div><div><ul><li><div>
Basic understanding of AI/ML (including GenAI) and data governance, Models, MLOps, Agents, MCP, A2A and technology governance/risk/compliance principles.</div></li></ul></div><div><ul><li><div>
Familiarity with using AI-assisted coding/prototyping tools (GitHub Copilot, Claude Code etc.) to product, iterate on prototypes, PRDs and technical concepts in close partnership with engineering and design.</div></li></ul></div><div><ul><li><div>
Proven experience in business analysis to identify critical requirements by understanding complex and interdependent processes.
</div></li></ul></div></div><div><div><ul><li><div>Strong critical thinking and problem-solving skills, with the ability to identify and mitigate risks effectively.
</div></li></ul></div><div><ul><li><div>Excellent presentation and communication skills, with the ability to convey complex information to senior leaders and stakeholders.
</div></li></ul></div><div><ul><li><div>Proven ability to collaborate effectively across cross-functional teams and build strong working relationships.
</div></li></ul></div><div></div><div><div><b>Preferred qualifications, capabilities and skills</b>
</div></div><div><ul><li><div>Experience with public cloud platforms (e.g., AWS, GCP, Azure) is a plus.</div></li></ul></div><div><ul><li><div>
Demonstrated a track record of building end-to-end prototypes with AI assistance and translating them into engineering-ready acceptance criteria; strong experience with AI coding assistants.</div></li></ul></div><div><ul><li><div>
Computer Science undergrad/grad degree and ideally experience working as an engineer in Financial Services with a focus on building AI products.</div></li></ul></div><div><ul><li><div>
Certifications in AI governance, data governance, or related fields.</div></li></ul></div></div><div><br>
</div><div></div><br>
<b>ABOUT US</b><br>
<br>
<br>
<div><div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><p></p><div><p>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
</p><div><p>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. Visit our FAQs for more information about requesting an accommodation.</p>
<p>JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans</p><br>
</div></div></div><br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

AI Product Manager - Governance (Senior Associate)

Nebius

<div><div><p><b>About Nebius:</b></p>
<p>
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.</p>
<p>
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.</p>
<p>
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&amp;D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&amp;D.</p></div><div>
<p><b>
About Tavily</b><br>
<br>
We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent - but also informed.</p>
<p>
We work with some of the most innovative teams in AI - from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world.</p>
<p><b>
Role:</b></p>
</div>
<p>We are looking for a Senior Business Systems Engineer to own our GTM Operations systems and strategy. You will have an integral role in architecting the engine that powers Tavily's growth. You will be our first hire to this team, building a seamless, scalable GTM stack and ensuring our data architecture supports world-class execution across Sales, Marketing, and Finance.</p>
<ul>
<li>Own the end-to-end technical architecture of the GTM tech stack, ensuring seamless data flow across the entire customer lifecycle&mdash;from initial marketing lead to sales conversion and customer success renewal. We will be implementing a fresh SFDC instance which you will help create from the ground up.</li>
</ul><ul><li>Serve as the primary technical liaison for Sales, Finance, and Marketing leadership, translating complex departmental requirements into a multi-quarter technical roadmap for the Force.com platform and integrated ecosystem.</li>
</ul><ul><li>Establish and enforce rigorous engineering standards, including automated testing and security protocols to ensure the reliability and integrity of internal GTM applications.</li>
</ul>
<p><b>What We're Looking For (Must Have):</b></p>
<ul>
<li>6+ years of Force.com development experience with a deep understanding of Apex, LWC, and platform limits.</li>
</ul><ul><li>Proven track record of designing complex enterprise integrations and managing high-volume data pipelines.</li>
</ul><ul><li>BS/MS in Computer Science, Computer Engineering, or a related technical field.</li>
</ul><ul><li>Ability to navigate complex relational databases and leverage data for strategic decision-making.</li>
</ul><ul><li>Experience with Agile methodologies and managing a prioritized backlog in Jira or similar tools.</li>
</ul>
<p><b>Nice to have:</b></p>
<ul>
<li>Salesforce Certified Application or System Architect.</li>
</ul><ul><li>Deep experience with CPQ and Billing, Stripe, or Netsuite integrations.</li>
</ul><ul><li>Advanced expertise in Integration Platforms like Workato, Zapier or Mulesoft.</li>
</ul><div><p><b>
Benefits &amp; Perks:</b></p>
<ul>
<li>Competitive compensation</li>
<li>Career growth and learning opportunities</li>
<li>Flexibility and ownership</li>
<li>Collaborative and innovative culture</li>
<li>Opportunity to work on impactful AI projects</li>
<li>International environment and talented teams</li>
</ul>
<p><b>What's it like to work at Nebius:</b></p>
<p>
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI</p>
<p><b>
Equal Opportunity Statement:</b></p>
<p>
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.</p>
<p>
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.</p>
<p>
If you need accommodations during the application process, please let us know.</p></div></div>

Senior Business Systems Engineer (Agentic Search) - Tavily

Giga

<div>
 <strong>
  About Giga
  <br/>
  <br/>
 </strong>
 Giga has recently raised a $61M Series A and has several paying customers, including DoorDash. We&rsquo;re building the next generation of customer experience &mdash; real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world&rsquo;s largest enterprises.
 <br/>
 <br/>
 It&rsquo;s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.
 <br/>
 <br/>
 The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:
 <br/>
 <br/>
 <ul>
  <li>
   Voice AI startup Giga raises $61M Series A
  </li>
  <li>
   DoorDash and Giga Partnership
   <br/>
   <br/>
  </li>
 </ul>
 Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 We're looking for software engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers who will help you grow.
 <br/>
 <br/>
 This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.
 <br/>
 <br/>
 <strong>
  What You'll Work On
  <br/>
  <br/>
 </strong>
 You'll contribute to projects across our stack. Some examples:
 <br/>
 <br/>
 <ul>
  <li>
   Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resources
  </li>
  <li>
   Activity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behavior
  </li>
  <li>
   Dynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pages
  </li>
  <li>
   Agent memory: Conversation awareness and recent interaction lookups so agents remember context across sessions
   <br/>
   <br/>
  </li>
 </ul>
 As an early-career engineer, you'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.
 <br/>
 <br/>
 <strong>
  You Might Be a Fit If You
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have 1-3 years of professional software engineering experience
  </li>
  <li>
   Are curious and ask good questions&mdash;you want to understand why things work, not just how
  </li>
  <li>
   Can take feedback well and iterate quickly
  </li>
  <li>
   Prefer shipping over perfection but still care about quality
  </li>
  <li>
   Want to grow at a startup where you'll have real responsibility early
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Perks &amp; Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive base + bonus + equity
  </li>
  <li>
   Catered lunch daily
  </li>
  <li>
   Dinner stipend
  </li>
  <li>
   $500/month wellness &amp; commuter benefit (gym, fitness classes, mental health)
  </li>
  <li>
   401(k) plan
  </li>
  <li>
   Medical, dental, and vision coverage
   <br/>
   <br/>
  </li>
 </ul>
 Giga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
 <br/>
 <br/>
 Compensation Range: $160K - $250K
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 <br/>
</div>


Software Engineer I / II

Commure

<div><p>At Commure, we're building the AI Operating System for healthcare, the foundation that defines how care is delivered, documented, and financed. Our platform spans the full care journey: Ambient AI and Dictation eliminating documentation burden at the point of care, intelligent Agents automating patient and revenue workflows, and autonomous RCM processing billions in claims, all on a single AI-native platform integrated with 60+ EHRs.</p><p></p><p>
Healthcare carries a $1 trillion administrative burden and we're at the center of transforming it. Today, 500,000+ clinicians across 500+ healthcare organizations nationwide trust Commure to handle $25B+ in annual claims and support over 200 million patient interactions. Our latest $70M raise at a $7B valuation reflects the confidence the market has placed in this mission.</p><p></p><p>
Our team works directly alongside clinicians, not through layers of process, which means the gap between what you build and its impact on patient care is immediate. We move fast, deploy daily, and take full ownership from early thinking to production. If you're energized by hard problems, high stakes, and a team that holds itself to a high bar, you'll find your people here.</p><p></p><p>
The future of healthcare is being built right now. Come deliver this transformation.</p><p></p><p><b>
About the Role</b></p><p>
At Commure, the AI Integration Team plays a crucial role in supporting the company&rsquo;s core products, Revenue Cycle Management (RCM) and Ambient, by ensuring seamless data flow between our platform and over 40 Electronic Medical Records (EMRs). This team is responsible for fetching vital Encounter and Appointment data from multiple EMRs and, when necessary, writing data back to these systems. The team's work ensures the interoperability and smooth exchange of healthcare data via HL7, enabling healthcare providers to deliver more efficient and accurate care while streamlining administrative processes. We're looking for a Senior Software Engineer who takes ownership end-to-end, moves fast, and wants their work to directly impact how care is delivered.</p><p></p><p><b>
What You'll Do</b></p><ul><li><p>
Design and implement complex integration solutions between our platform and third-party healthcare systems (EHRs, insurance providers, etc.) while ensuring high performance, reliability, and scalability.</p></li><li><p>
Utilize the latest developments in LLM technology to automate the reverse-engineering of electronic health records.</p></li><li><p>
Collaborate with cross-functional teams (product, engineering, and healthcare) to gather integration requirements, define technical approaches, and prioritize tasks based on business needs.</p></li><li><p>
Contribute to the technical direction of the integration platform by proposing and implementing improvements to architecture, tools, and technologies.</p></li><li><p>
Take ownership of end-to-end integration workflows, from design and development through to deployment and post-launch monitoring.</p></li><li><p>
Identify and resolve performance bottlenecks, troubleshoot integration issues, and proactively improve the reliability of integrations in production environments.</p></li><li><p>
Ensure all integration work adheres to healthcare compliance and security standards (e.g., HIPAA, HL7, FHIR) and collaborate with security teams to protect sensitive data.</p></li><li><p>
Work closely with junior engineers to provide technical guidance and mentorship, helping them solve problems and ensuring high-quality code standards are followed.</p></li><li><p>
Drive the implementation of best practices for integration development, including testing, error handling, version control, and continuous integration.</p></li><li><p>
Collaborate with DevOps and QA teams to implement monitoring and alerting systems that ensure integration reliability and system health in production.</p></li><li><p>
Stay up-to-date with industry trends in healthcare technology, integration patterns, and emerging tools, continuously suggesting and applying innovations that can improve system performance and integration capabilities.</p></li><li><p>
Participate in agile development cycles, contributing to sprint planning, retrospectives, and maintaining a collaborative and efficient working environment</p></li></ul><p></p><p><b>
What You Have</b></p><ul><li><p>
[Required] Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related field, or equivalent extensive experience</p></li><li><p>
5+ years of professional software development industry experience</p></li><li><p>
Proficiency in backend languages like Python, Go, or C++.</p></li><li><p>
Proficiency in frontend languages like Javascript, HTML, CSS</p></li><li><p>
Experience including but not limited to Git, GCP / AWS, Docker, Kubernetes, relational and non-relational DBs, and monitoring/alerting tools</p></li><li><p>
Proven track record of designing and implementing end-to-end solutions and making successful architectural decisions</p></li><li><p>
Excellent communication and collaboration skills, with the ability to work in a fast-paced, dynamic environment.</p></li></ul><p></p><p>
Please be aware that all official communication from us will come exclusively from email addresses ending in <b>@</b><b>getathelas.com</b>, <b>@</b><b>commure.com</b> or <b>@</b><b>augmedix.com</b>.<b> </b>Any emails from other domains are not affiliated with our organization.</p><p><br>
Employees will act in accordance with the organization&rsquo;s information security policies, to include but not limited to protecting assets from unauthorized access, disclosure, modification, destruction or interference nor execute particular security processes or activities. Employees will report to the information security office any confirmed or potential events or other risks to the organization. Employees will be required to attest to these requirements upon hire and on an annual basis.</p><p>
Compensation Range: $170K - $240K</p></div>

Senior Software Engineer, AI Integrations

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